DBMS > Apache Phoenix vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. PostgreSQL
System Properties Comparison Apache Phoenix vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. PostgreSQL
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | Apache Phoenix Xexclude from comparison | IBM Db2 Event Store Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Microsoft SQL Server Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A scale-out RDBMS with evolutionary schema built on Apache HBase | Distributed Event Store optimized for Internet of Things use cases | Fully managed big data interactive analytics platform | Microsofts flagship relational DBMS | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Event Store Time Series 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 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 engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Graph DBMS Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Website | phoenix.apache.org | www.ibm.com/products/db2-event-store | azure.microsoft.com/services/data-explorer | www.microsoft.com/en-us/sql-server | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | phoenix.apache.org | www.ibm.com/docs/en/db2-event-store | docs.microsoft.com/en-us/azure/data-explorer | learn.microsoft.com/en-US/sql/sql-server | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation | IBM | Microsoft | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2014 | 2017 | 2019 | 1989 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.0-HBase2, July 2018 and 4.15-HBase1, December 2019 | 2.0 | cloud service with continuous releases | SQL Server 2022, November 2022 | 16.3, May 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2.0 | commercial free developer edition available | commercial | commercial restricted free version is available | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant. |
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C and C++ | C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux Unix Windows | Linux Linux, macOS, Windows for the developer addition | hosted | Linux Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes late-bound, schema-on-read capabilities | 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. | no | no | yes | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | all fields are automatically indexed | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | yes through the embedded Spark runtime | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC | ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET JDBC ODBC OLE DB Tabular Data Stream (TDS) | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C C# C++ Go Groovy Java PHP Python Scala | C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic | .Net Go Java JavaScript (Node.js) PowerShell Python R | C# C++ Delphi Go Java JavaScript (Node.js) PHP Python R Ruby Visual Basic | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions | yes | Yes, possible languages: KQL, Python, R | Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding Implicit feature of the cloud service | tables can be distributed across several files (horizontal partitioning); sharding through federation | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication Source-replica replication | Active-active shard replication | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | yes, but depending on the SQL-Server Edition | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Hadoop integration | 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 or Eventual Consistency | Eventual Consistency | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | No - written data is immutable | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy | fine grained access rights according to SQL-standard | Azure Active Directory Authentication | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendorWe invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3rd parties | Navicat for SQL Server gives you a fully graphical approach to database management and development. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for SQL Server and many other database management systems. » more | Instaclustr: Fully Hosted & Managed PostgreSQL » more Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance. » more 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! » more pgDash: In-Depth PostgreSQL Monitoring. » more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more CYBERTEC is your professional partner in PostgreSQL topics for over 20 years. As our main aim is to be your single-source all-in-one IT service provider, we offer a wide range of products and services. Visit our website for more details. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more Redgate webinars: A series of key topics for new PostgreSQL users. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Apache Phoenix | IBM Db2 Event Store | Microsoft Azure Data Explorer | Microsoft SQL Server | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cloudera's HBase PaaS offering now supports Complex Transactions | MySQL is the DBMS of the Year 2019 The struggle for the hegemony in Oracle's database empire Microsoft SQL Server is the DBMS of the Year | 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 Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services Bridge the SQL-NoSQL gap with Apache Phoenix Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag Deep dive into Azure HDInsight 4.0 provided by Google News Advancements in streaming data storage, real-time analysis and machine learning IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere How IBM Is Turning Db2 into an 'AI Database' Best cloud databases of 2022 Why a robust data management strategy is essential today | IBM HDM provided by Google News Azure Data Explorer: Log and telemetry analytics benchmark Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Controlling costs in Azure Data Explorer using down-sampling and aggregation 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 A generative AI use case using Amazon RDS for SQL Server as a vector data store | Amazon Web Services SQL Server vNext: When and What Is Coming Data Virtualization in SQL Server 2022 SQL Server 2014 end of support: Keep your customers secure How to Know When It's Time for a Microsoft SQL Server Upgrade provided by Google News Enterprise DB begins rolling AI features into PostgreSQL Deep PostgreSQL Thoughts: Valuing Currency EDB unveils EDB Postgres AI Nutanix partners with EDB to fit database service for AI – Blocks and Files Addressing PostgreSQL Vulnerabilities in Ubuntu provided by Google News |
Share this page