DBMS > Greenplum vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. mSQL vs. PostgreSQL
System Properties Comparison Greenplum vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. mSQL vs. PostgreSQL
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| Name | Greenplum Xexclude from comparison | IBM Db2 warehouse  formerly named IBM dashDB Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | mSQL Mini SQL Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image. | Cloud-based data warehousing service | Fully managed big data interactive analytics platform | mSQL (Mini SQL) is a simple and lightweight RDBMS | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Relational DBMS | Relational DBMS column oriented | Relational DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store Spatial DBMS | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engineTime Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | greenplum.org | www.ibm.com/products/db2/warehouse | azure.microsoft.com/services/data-explorer | hughestech.com.au/products/msql | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.greenplum.org | docs.microsoft.com/en-us/azure/data-explorer | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Pivotal Software Inc. | IBM | Microsoft | Hughes Technologies | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2005 | 2014 | 2019 | 1994 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 7.0.0, September 2023 | cloud service with continuous releases | 4.4, October 2021 | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source Apache 2.0 | commercial | commercial | commercial free licenses can be provided | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | yes | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux | hosted | hosted | AIX HP-UX Linux OS X Solaris SPARC/x86 Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | yes | Fixed schema with schema-less datatypes (dynamic) | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | yes | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | yes since Version 4.2 | no Import/export of XML data possible | yes | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | yes | all fields are automatically indexed | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | yes | Kusto Query Language (KQL), SQL subset | A subset of ANSI SQL is implemented no subqueries, aggregate functions, views, foreign keys, triggers | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | JDBC ODBC | .NET Client API JDBC ODBC OLE DB | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | JDBC ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Supported programming languages | C Java Perl Python R | Java JavaScript (Node.js) Perl PHP Python R Ruby | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C++ Delphi Java Perl PHP Tcl | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | PL/SQL, SQL PL | Yes, possible languages: KQL, Python, R | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | yes | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding Implicit feature of the cloud service | none | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | yes | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | none | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | yes | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Eventual Consistency Immediate Consistency | none | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | yes | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | no | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | no | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| 3rd parties | Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today!
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| Greenplum | IBM Db2 warehouse formerly named IBM dashDB | Microsoft Azure Data Explorer | mSQL Mini SQL | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services 1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book] RSA: EMC integrates Hadoop with Greenplum database Greenplum 6 ventures outside the analytic box | ZDNET Greenplum 6 review: Jack of all trades, master of some provided by Google News Announcing the deprecation of prior generation Db2 Warehouse plans on AWS Introducing the next generation of Db2 Warehouse: Our cost-effective, cloud-native data warehouse built for always-on ... Db2 Warehouse delivers 4x faster query performance than previously, while cutting storage costs by 34x Data mining in Db2 Warehouse: the basics Top 7 Cloud Data Warehouse Companies provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Controlling costs in Azure Data Explorer using down-sampling and aggregation Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Microsoft Introduces Azure Integration Environments and Business Process Tracking in Public Preview Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services provided by Google News Higher Education PS rules out ghost students before PAC provided by Google News How to implement a better like, views, comment counters in PostgreSQL? How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need At Build, Microsoft Fabric, PostgreSQL and Cosmos DB get AI enhancements Oracle Introduces PostgreSQL Running Native on OCI provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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