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  • Using Keep-Alives To Ensure Long-Running MySQL & MariaDB Sessions Stay Connected
    Overview The Skinny In this blog post we will discuss how to use the Tungsten Connector keep-alive feature to ensure long-running MySQL & MariaDB/Percona Server client sessions stay connected in a Tungsten Cluster. Agenda What’s Here? Briefly explore how the Tungsten Connector works Describe the Connector keep-alives – what are they and why do we use them? Discuss why the keep-alive feature is not available in Bridge mode and why Examine how to tune the keep-alive feature in the Tungsten Connector Tungsten Connector: A Primer A Very Brief Summary The Tungsten Connector is an intelligent MySQL database proxy located between the clients and the database servers, providing a single connection point, while routing queries to the database servers. √ High-Availability The most important function of the Connector is failover handling. In the event of a failure, the Tungsten Connector can automatically route queries away from the failed server and towards servers that are still operating. When the cluster detects a failed master because the MySQL server port is no longer reachable, the Connectors are signaled and traffic is re-routed to the newly-elected Master node. √ Read-Scaling Next is the ability to provide read-scaling and route MySQL queries based on various factors. During the routing process, Tungsten Connector communicates with the Tungsten Manager to determine which datasources are the most up to date, and their current role so that the packets can be routed properly. In the default Bridge mode, traffic is routed at the TCP layer, and read-only queries must be directed to a different port (normally 3306 for writes and 3307 for reads). There are additional modes, Proxy/Direct and Proxy/SmartScale. In both cases, queries are intercepted and inspected by the Connector. The decisions made are tunable based on configuration parameters. For more detailed information about how the Tungsten Connector works, please read our blog post, “Experience the Power of the Tungsten Connector” For a comparison of Routing methods, please see the documentation page: http://docs.continuent.com/tungsten-clustering-6.0/connector-routing-types.html Tungsten Connector: Keep-Alives What are they and why do we use them? Connections to MySQL servers can automatically time-out according to the wait_timeout variable configured within the MySQL server. To prevent these connections being automatically closed, the connector can be configured to keep the connection alive by submitting a simple SELECT statement (actually SELECT ‘KEEP_ALIVE’;) periodically to ensure that the MySQL timeout is not reached and the connection closed. The keep-alive feature was designed with Proxy modes in mind (Proxy/Direct and Proxy/SmartScale). When using either, Proxy mode, every single client connection gets 2 mysql server-side connections: one for reads and one for writes. If your application is read-intensive, the server-side read-only connection gets updated often and is kept alive by MySQL. Under those conditions, the write connection is NOT being unused, and so there is a risk the MySQL server’s wait_timeout to expire, so the next write on the client side connection would get an error. In response to the above scenario, the keep-alive feature was implemented. Keep-alives by default are enabled and set to autodetect, which will compute suitable values based on the MySQL server wait_timeout in order to be totally transparent to the application. This design will produce the exact same behavior as if the application were connected directly to the database server. Keep-Alives and Bridge Mode Why They Do Not Work Together The Connector Keep-alive feature is NOT compatible with Bridge mode. In Bridge mode, the client session is directly connected to the MySQL server at the TCP level, literally forwarding the client’s packet to the server. This means that closing connections is the responsibility of the MySQL server based on the configured wait_timeout value, not the Connector. Summary The Wrap-Up In this blog post we discussed the basics of the Tungsten Connector, the Keep-alive feature and how to tune the values that control it. To learn about Continuent solutions in general, check out https://www.continuent.com/solutions The Library Please read the docs! For more information about Tungsten Connector Keep-alives, please visit http://docs.continuent.com/tungsten-clustering-6.0/connector-states-keepalive.html Tungsten Clustering is the most flexible, performant global database layer available today – use it underlying your SaaS offering as a strong base upon which to grow your worldwide business! For more information, please visit https://www.continuent.com/solutions Want to learn more or run a POC? Contact us.

  • Meet Codership, the makers of Galera Cluster, at DataOps Barcelona 20-21 June
    Codership, the makers of Galera Cluster are proud to be sponsors at the second annual DataOps.Barcelona happening June 20-21 2019 at the World Trade Centre in Barcelona, Spain. For an opening keynote, in the Auditorium from 9.30-10.30am see Colin Charles speak about What’s New in Galera Cluster 4. There are plenty of new features and it debuts in MariaDB Server 10.4, so expect to hear a lot about what is available. On day two, Colin will also speak about Running MySQL and MariaDB Server securely in 2019. Our booth will have Vlad Alexandru manning it all the time, and we would love to talk to you about Galera Cluster, roadmaps, plans, as well as our support, training and consulting for Galera Cluster for MySQL as well as Percona XtraDB Cluster (PXC). Galera Cluster will also be running a raffle, so drop by Galera Cluster booth, chat with our friendly folk, and be in the running to win a pair of Bose noise cancelling headphones!

  • SQL JOINS Tutorial For Beginners | SQL JOINS Example
    SQL JOINS Tutorial For Beginners | SQL JOINS Example is today’s topic. SQL is the special-purpose programming language designed for managing information in the relational database management system (RDBMS). The word relational is key; it specifies that the DBMS is organized in such a way that there are clear relations defined between the different sets of data. SQL joins are used to combine the records from two or more tables in a database. SQL JOIN clause is used to combine the rows from two or more tables, based on a related column between them. SQL JOINS Tutorial For Beginners Different types of joins are: INNER JOIN LEFT JOIN RIGHT JOIN FULL JOIN CROSS JOIN SELF JOIN #INNER JOINS in SQL SQL Inner Join is used to select all the rows from tables for the match between the columns in tables. SQL INNER JOIN is based on the concept of EQUI JOINS. EQUI JOINS are those who use the comparison operator (=) for combining records from two or more tables. When the condition is satisfied, column values for each matched pair of rows of two tables are combined into a result row.   The shaded part above Shows a common records between both the tables. SYNTAX Select columns from Table_1 INNER JOIN Table_2 on Table_1.column = Table_2.column; So, in the above statements columns represent the column names of the tables. Table_1 and Table_2 are the names of tables. And the condition i.e Table_1.column = Table_2.column is used to compare the columns which are common in both the tables. Table_1: Employee Emp_id Emp_name City State Salary 101 Rohit Patna Bihar 30000 201 Shivam Jalandhar Punjab 20000 301 Karan Allahabad Uttar Pradesh 40000 401 Suraj Kolkata West Bengal 60000 501 Akash Vizag Andhra Pradesh 70000   Table_2: Department Dept_no Emp_id 123 301 214 401 125 505   See the following query. Select Department.Dept_no, Employee.Emp_name, Employee.City, Employee.Salary from Department INNER JOIN Employee on Department.Emp_id = Employee.Emp_id;   #Left Join in SQL Left outer join returns all rows in the table which is on the left side matched with the rows of a table in right side. This gives the conclusion that the SQL left Join always contains the rows in the left table.   The above Venn diagram shows that the left table rows will always be displayed whether the conditions match or not. SYNTAX Select column_1, column_2… from table_1 LEFT JOIN table_2 ON CONDITION; See the following tables. CUSTOMER: ID NAME AGE CITY 1 Rohit 20 Patna 2 Shivam 18 Jalandhar 3 Pranav 19 Dharamshala   ORDERS: O_ID Cust_ID City AMOUNT 201 1 Patna 3000 202 2 Jalandhar 4000 203 4 Kolkata 1000   Let’s clear this with an example. Select Orders.O_ID, Customer.id, customer.name, Orders.amount From CUSTOMER LEFT JOIN Orders ON Customer.ID = Orders.Cust_ID; See the following output.   As you can see, all the contents of a left table are displayed, whether it is matched with a right table or not. Right table contents which are matched with the left table is displayed as well and which are not matched is displayed with NULL values. #RIGHT JOIN in SQL The SQL right join returns all the values from the rows of a right table. It also includes a matched values from a left table, but if there is no matching in both the tables, it returns the NULL values.   The above Venn diagram illustrates that all the rows of the right table will be displayed whether the condition matches or not. SYNTAX Select column_1, column_2… from table_1 RIGHT JOIN table_2 ON CONDITION; CUSTOMER: ID NAME AGE CITY 1 Rohit 20 Patna 2 Shivam 18 Jalandhar 3 Pranav 19 Dharamshala   ORDERS: O_ID Cust_ID City AMOUNT 201 1 Patna 3000 202 2 Jalandhar 4000 203 4 Kolkata 1000   Query Select Orders.O_ID,Customer.id,customer.name,Orders.amount From CUSTOMER RIGHT JOIN Orders ON Customer.ID = Orders.Cust_ID; OUTPUT   EXPLANATION As you can see, all the contents of the right table are displayed, whether it is matched with a left table or not. Left table contents which are matched with a right table is displayed as well and which are not matched is displayed with the NULL values. #FULL JOIN in SQL SQL full join returns all the rows in the left table, right table and matching rows in both the tables or you can say it is a combination of left and right join. It is also known as a full outer join.   The above Venn diagram illustrates that all the rows of both the table will be displayed whether the conditions match or not. SYNTAX Select * from table1 FULL OUTER JOIN table2 ON CONDITION; Let’s consider a table. CUSTOMER: ID NAME AGE CITY 1 Rohit 20 Patna 2 Shivam 18 Jalandhar 3 Pranav 19 Dharamshala   ORDERS: O_ID Cust_ID City AMOUNT 201 1 Patna 3000 202 2 Jalandhar 4000 203 4 Kolkata 1000   Let’s clear this with an example. Select * from Customer FULL OUTER JOIN Orders ON Customer.ID = Orders.cust_id; OUTPUT The above Statement will not work in MySQL, Because the SQL full outer join returns the result set that is combined results of both SQL left join and SQL right join. So to generate the result, we have to use the UNION operator. Statement Select * from Customer LEFT JOIN Orders ON Customer.id = Orders.Cust_ID UNION Select * from Customer RIGHT JOIN Orders ON Customer.id = Orders.Cust_id; See the output.   #CROSS JOIN in SQL SQL Cross Join is used to join the table having no condition in which all the records of the first table comes with all the records of the second table. This type of Join is also called a Cartesian product. Unlike the INNER JOIN or LEFT JOIN, the cross join does not establish a relationship between the joined tables. NOTE: If Where Condition is not used with CROSS JOIN, then it will behave like a cartesian product.   Here arrows are pointing to the rows of a table. SYNTAX SELECT COLUMNS_NAME FROM TABLE_1 CROSS JOIN TABLE_2; Suppose there are two tables.   QUERY Select * from STUDENT CROSS JOIN COURSE; OUTPUT   All the combinations of rows are listed. #SELF JOIN in SQL In the self join table is joined itself, i.e. each row is joined with itself and all other rows depending on the conditions.   Syntax SELECT a.column1, b.column2 from table_name a, table_name b where condition; Table: (Employee) Emp_id Emp_name City State Salary 101 Rohit Patna Bihar 30000 201 Shivam Jalandhar Punjab 20000 301 Karan Allahabad Uttar Pradesh 40000 401 Suraj Kolkata West Bengal 60000 501 Akash Vizag Andhra Pradesh 70000   QUERY Select a.emp_name,b.salary from employee a,employee b where a.salary < b.salary; OUTPUT   Finally, SQL JOINS Tutorial For Beginners | SQL JOINS Example is over. The post SQL JOINS Tutorial For Beginners | SQL JOINS Example appeared first on AppDividend.

  • Our recap of the Percona Live Conference in Austin
    We were pleased to sponsor the Percona Live Conference in Austin this year: many thanks to the Percona Team for organising a smooth conference yet again! This is the recap of our week in Texas! At The Conference This year’s conference was the first one not taking place in Santa Clara, CA, but rather in Austin, TX. This turned out to be a nice choice by Percona, as it meant that open source database users who may not have travelled to California in the past, were attracted to the new location; and Austin being the new hot spot for (tech) companies at the moment, a lot of “locals” seemed to have made the choice to attend the conference. It was great to meet many new faces as a result. As Diamond Sponsors of the conference we were of course present with a booth in the exhibition hall, as well as with three talks. And while the hotel looked slightly dystopian at night, it was in fact a nice and pleasant location to spend the week. Our Announcements We had a couple of announcements that coincided with the Percona Live conference week and it was great to be able to present and discuss these with the attendees ‘hot off the press’ on site. New Tungsten Replicator (AMI) First off, we announced the immediate availability of the new Tungsten Replicator (AMI). Tungsten Replicator (AMI) is a replication engine that provides high-performance and improved replication functionality over the native MySQL replication solution and provides an ability to apply real-time MySQL data feed into a range of analytics and big data databases. Users can now replicate directly from AWS Aurora, AWS RDS MySQL, MySQL, MariaDB & Percona Server into popular analytic repositories such as MySQL (all variations), PostgreSQL, AWS RedShift, Kafka and Vertica​ from as little as $0.50/hour. Find out more in our announcement blog. New Partnership for MySQL & MariaDB Availability Solutions with Datavail We were also happy to announce a new partnership with Datavail to provide solutions for continuous & highly available MySQL, Percona Server & MariaDB database operations based on Tungsten Clustering & Datavail Database Services. Datavail is a renowned, tech-enabled data management, applications, business intelligence, and software solutions provider with a team of 700+ DBAs that look after customers’ database environments. Find out more on the partnership announcement. Our (And One Of Our Customer’s) Talks The Color of Open Source Money – Are some open source business models more acceptable than others? By Eero Teerikorpi, Founder & CEO The color of open source money is much discussed these days, and with this talk, Eero examines some of the aspects of it a little closer, and offers his perspective on the different shades of open source money and acceptable balance on commercial efforts to justify the investments needed for the sustainability of a given project. Watch the recording of the talk below: https://continuent-videos.s3.amazonaws.com/Eero_Keynote_Percona_Live_Austin_2019.mp4 Moving Data in real-time into Amazon Redshift By Matthew Lang, Director Professional Services Amazon Redshift has been providing scalable, quick-to-access analytics platforms for many years, but the question remains: how do you get the data from your existing datastore into Redshift for processing? Find out by reading the slides to the talk below: Download Redshift Slides Building geo clusters with AWS Aurora – can we make it better? By Matthew Lang, Director Professional Services In this talk, our colleague Matt explores how to build and deploy a geo-scale MySQL / MariaDB / Percona cloud back-end by covering these three key topics: Overview of Amazon Aurora cross region Common challenges when using Amazon Aurora How can multi-region MySQL / MariaDB / Percona deployments be improved? Find out more about these topics by going through the slides below: Download Aurora Slides Globalizing Player Accounts with MySQL at Riot Games Tyler Turk, Senior Infrastructure Engineer In this talk, Tyler briefly overviews the evolution of the Riot Games player accounts services from legacy isolated datacenter deployments to a globally replicated database cluster fronted by their account services and outlines some of the growing pains and experiences that got them to where they are today. Access Riot Games Slides Here What Also Happened At the Conference For this year’s Community Dinner, PlanetScale and Percona invited us to a unique view of Austin by taking attendees to the water. As one of the best ways to see the famous Austin bat colonies, they’d arranged a dusk-time river cruise on the Lone Star River Boat, which was a very enjoyable way to experience the city from a different perspective (though the bats mostly decided to stay put that evening). And speaking of the famous Austin bats: we finished the conference by patiently waiting for the bats to appear from inside and under the bridge near the conference hotel, where they live. It took a couple of hours on the Thursday evening, but it was well worth the wait. Thanks to everyone who attended, spoke at, organised and sponsored the conference: we’re looking forward to hopefully seeing you all again at the next one

  • 2019 Open Source Database Report: Top Databases, Public Cloud vs. On-Premise, Polyglot Persistence
    Ready to transition from a commercial database to open source, and want to know which databases are most popular in 2019? Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Or, considering adding a new database to your application and want to see which combinations are most popular? We found all the answers you need at the Percona Live event last month, and broke down the insights into the following free trends reports: Top Databases Used: Open Source vs. Commercial Cloud Infrastructure Analysis: Public Cloud vs. On-Premise vs. Hybrid Cloud Polyglot Persistence Trends: Number of Databases Used & Top Combinations 2019 Top Databases Used So, which databases are most popular in 2019? We broke down the data by open source databases vs. commercial databases: Open Source Databases Open source databases are free community databases with the source code available to the general public to use, and may be modified or used in their original design. Popular examples of open source databases include MySQL, PostgreSQL and MongoDB. Commercial Databases Commercial databases are developed and maintained by a commercial business that are available for use through a licensing subscription fee, and may not be modified. Popular examples of commercial databases include Oracle, SQL Server, and DB2. Top Open Source Databases MySQL remains on top as the #1 free and open source database, representing over 30% of open source database use. This comes as no surprise, as MySQL has held this position consistently for many years according to DB-Engines. PostgreSQL came in 2nd place with 13.4% representation from open source database users, closely followed by MongoDB at 12.2% in 3rd place. This again could be expected based on the DB-Engines Trend Popularity Ranking, but we saw MongoDB in 2nd place at 24.6% just three months ago in our 2019 Database Trends – SQL vs. NoSQL, Top Databases, Single vs. Multiple Database Use report. What are the Top Open Source Databases in 2019? #SQL #NoSQLClick To Tweet While over 50% of open source database use is represented by the top 3, we also saw a good representation for #4 Redis, #5 MariaDB, #6 Elasticsearch, #7 Cassandra, and #8 SQLite. The last 2% of databases represented include Clickhouse, Galera, Memcached, and Hbase. Top Commercial Databases In this next graph, we’re looking at a unique report which represents both polyglot persistence and migration trends: top commercial databases used with open source databases. We’ve been seeing a growing trend of leveraging multiple database types to meet your application needs, and wanted to compare how organizations are using both commercial and open source databases within a single application. This report also represents the commercial database users who are also in the process of migrating to an open source database. For example, PostgreSQL, the fastest growing database by popularity for 2 years in a row, has 11.5% of its user base represented by organizations currently in the process of migrating to PostgreSQL. So, now that we’ve explained what this report represents, let’s take a look at the top commercial databases used with open source. Oracle, the #1 database in the world, holds true representing over 2/3rds of commercial and open source database combinations. What is shocking in this report is the large gap between Oracle and 2nd place Microsoft SQL Server, as it maintains a much smaller gap according to DB-Engines. IBM Db2 came in 3rd place representing 11.1% of commercial database use combined with open source. Cloud Infrastructure Breakdown by Database Now, let’s take a look at the cloud infrastructure setup breakdown by database management systems. Public Cloud vs. On-Premise vs. Hybrid Cloud We asked our open source database users how they’re hosting their database deployments to identify the current trends between on-premise vs. public cloud vs. hybrid cloud deployments. A surprising 49.5% of open source database deployments are run on-premise, coming in at #1. While we anticipated this result, we were surprised at the percentage on-premise. In our recent 2019 PostgreSQL Trends Report, on-premise private cloud deployments represented 59.6%, over 10% higher than this report. Public cloud came in 2nd place with 36.7% of open source database deployments, consistent with the 34.8% of deployments from the PostgreSQL report. Hybrid cloud, however, grew significantly from this report with 13.8% representation from open source databases vs. 5.6% of PostgreSQL deployments. So, which cloud infrastructure is right for you? Here’s a quick intro to public cloud vs. on-premise vs. hybrid cloud: Which Cloud Infrastructure is Most Popular for Databases? Public Cloud vs. On-Premise vs. Hybrid CloudClick To Tweet Public Cloud Public cloud is a cloud computing model where IT services are delivered across the internet. Typically purchased through a subscription usage model, public cloud is very easy to setup with no large upfront investment requirements, and can be quickly scaled as your application needs change. On-Premise On-premise, or private cloud deployments, are cloud solutions dedicated to a single organization run in its own datacenter (or with a third-party vendor off-site). There are many more opportunities to customize your infrastructure with an on-premise setup, but requires a significant upfront investment in hardware and software computing resources, as well as on-going maintenance responsibilities. These deployment types are best suited for organizations with advanced security needs, regulated industries, or large organizations. Hybrid Cloud A hybrid cloud is a mixture of both public cloud and private cloud solutions, integrated into a single infrastructure environment. This allows organizations to share resources between public and private clouds to improve their efficiency, security, and performance. These are best suited for deployments that require the advanced security of an on-premise infrastructure, as well as the flexibility of the public cloud. Now, let’s take a look at which cloud infrastructures are most popular by each open source database type. Open Source Database Deployments: On-Premise In this graph, as well as the public cloud and hybrid cloud graphs below, we break down each individual open source database by the percentage of deployments that leverage this type of cloud infrastructure. So, which open source databases are most frequently deployed on-premise? PostgreSQL came in 1st place with 55.8% of deployments on-premise, closely followed by MongoDB at 52.2%, Cassandra at 51.9%, and MySQL at 50% on-premise. The open source databases that reported less than half of deployments on-premise include MariaDB at 47.2%, SQLite at 43.8%, and Redis at 42.9%. The database that is least often deployed on-premise is Elasticsearch at only 34.5%. Open Source Database Deployments: Public Cloud Now, let’s look at the breakdown of open source databases in the public cloud. SQLite is the most frequently deployed open source database in a public cloud infrastructure at 43.8% of their deployments, closely followed by Redis at 42.9%. MariaDB public cloud deployments came in at 38.9%, then 36.7% for MySQL, and 34.5% for Elasticsearch. Three databases came in with less than 1/3rd of their deployments in the public cloud, including MongoDB at 30.4%, PostgreSQL at 27.9%, and Cassandra with the fewest public cloud deployments at only 25.9%. Open Source Database Deployments: Hybrid Cloud Now that we know how the open source databases break down between on-premise vs. public cloud, let’s take a look at the deployments leveraging both computing environments. The #1 open source database to leverage hybrid clouds is Elasticsearch which is came in at 31%. The closest following database for hybrid cloud is Cassandra at just 22.2%. MongoDB was in 3rd for percentage of deployments in a hybrid cloud at 17.4%, then PostgreSQL at 16.3%, Redis at 14.3%, MariaDB at 13.9%, MySQL at 13.3%, and lastly SQLite at only 12.5% of deployments in a hybrid cloud. Open Source Database Deployments: Multi Cloud On average, 20% of public cloud and hybrid cloud deployments are leveraging a multi-cloud strategy. Multi-cloud is the use of two or more cloud computing services. We also took a look at the number of clouds used, and found that some deployments leverage up to 5 different cloud providers within a single organization: Most Popular Cloud Providers for Open Source Database Hosting In our last analysis under the Cloud Infrastructure breakdown, we analyze which cloud providers are most popular for open source database hosting: AWS is the #1 cloud provider for open source database hosting, representing 56.9% of all cloud deployments from this survey. Google Cloud Platform (GCP) came in 2nd at 26.2% with a surprising lead over Azure at 10.8%. Rackspace then followed in 4th representing 3.1% of deployments, and DigitalOcean and Softlayer followed last representing the remaining 3% of open source deployments in the cloud. Polyglot Persistence Trends Polyglot persistence is the concept of using different databases to handle different needs using each for what it is best at to achieve an end goal within a single software application. This is a great solution to ensure your application is handling your data correctly, vs. trying to satisfy all of your requirements with a single database type. An obvious example would be SQL which is good at handling structured data vs. NoSQL which is best used for unstructured data. Let’s take a look at a couple polyglot persistence analyses: Average Number of Database Types Used On average, we found that companies leverage 3.1 database types for their applications within a single organization. Just over 1/4 of organizations leverage a single database type, with some reporting up to 9 different database types used:   On Average, Apps Leverage 3.1 Different Database Types - See the On-Premise vs. Public Cloud BreakdownClick To Tweet Average Number of Database Types Used by Infrastructure So, how does this number break down across infrastructure types? We found that hybrid cloud deployments are most likely to leverage multiple database types, and average 4.33 database types at a time. On-premise deployments typically leverage 3.26 different database types, and public cloud came in lowest at 3.05 database types leverage on average within their organization. Databases Types Most Commonly Used Together Let’s now take a closer look at the database types most commonly leveraged together within a single application. In the chart below, the databases in the left column represent the sample size for that database type, and the databases listed on top are represent the percentage combined with that database type. The blue highlighted cells represent 100% of deployment combinations, while yellow represents 0% of combinations. So, as we can see below in our database combinations heatmap, MySQL is our most frequently combined database with other database types. But, while other database types are frequently leveraged in conjunction with MySQL, that doesn’t mean that MySQL deployments are always leveraging another database type. This can be seen in the first row for MySQL, as these are lighter blue to yellow compared to the first column of MySQL which is shows a much higher color match to the blue representing 100% combinations. The cells highlighted with a black border represent the deployments leveraging only that one database type, where again MySQL takes #1 at 23% of their deployments using MySQL alone. We can also see a similar trend with Db2, where the bottom row for Db2 shows that it is highly leveraged with MySQL, PostgreSQL, Cassandra, Oracle, and SQL Server, but a very low percentage of other database deployments also leverage Db2, outside of SQL Server which also uses DB2 in 50% of those deployments. SQL vs. NoSQL Open Source Database Popularity Last but not least, we compare SQL vs. NoSQL for our open source database report. SQL represents over 3/5 of the open source database use at 60.6%, compare to NoSQL at 39.4%. SQL vs. NoSQL - Which Database Type is Most Popular in 2019? #MySQL #PostgreSQL #MongoDB #RedisClick To Tweet We hope these database trends were insightful and sparked some new ideas or validated your current database strategy! Tell us what you think below in the comments, and let us know if there’s a specific analysis you’d like to see in our next database trends report! Check out our other reports for more insight on what’s trending in the database space: 2019 PostgreSQL Trends Report: Private vs. Public Cloud, Migrations, Database Combinations & Top Reasons Used 2019 Database Trends – SQL vs. NoSQL, Top Databases, Single vs. Multiple Database Use  Latest PostgreSQL Trends: Most Time-Consuming Tasks & Important Metrics to Track