DBMS > Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere vs. TDengine
System Properties Comparison Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere vs. TDengine
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Name | Microsoft Azure Data Explorer Xexclude from comparison | Netezza Also called PureData System for Analytics by IBM Xexclude from comparison | PostgreSQL Xexclude from comparison | SAP SQL Anywhere formerly called Adaptive Server Anywhere Xexclude from comparison | TDengine Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Fully managed big data interactive analytics platform | Data warehouse and analytics appliance part of IBM PureSystems | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments | Time Series DBMS and big data platform | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | 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. | Relational DBMS | Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | azure.microsoft.com/services/data-explorer | www.ibm.com/products/netezza | www.postgresql.org | www.sap.com/products/technology-platform/sql-anywhere.html | github.com/taosdata/TDengine tdengine.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.microsoft.com/en-us/azure/data-explorer | www.postgresql.org/docs | help.sap.com/docs/SAP_SQL_Anywhere | docs.tdengine.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Microsoft | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | SAP formerly Sybase | TDEngine, previously Taos Data | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2019 | 2000 | 1989 1989: Postgres, 1996: PostgreSQL | 1992 | 2019 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | cloud service with continuous releases | 16.3, May 2024 | 17, July 2015 | 3.0, August 2022 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial | Open Source BSD | commercial | Open Source AGPL V3, also commercial editions available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux included in appliance | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | AIX HP-UX Linux OS X Solaris Windows | Linux Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Fixed schema with schema-less datatypes (dynamic) | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | yes | yes | 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 | yes specific XML-type available, but no XML query functionality. | yes | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | all fields are automatically indexed | yes | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | yes | Standard SQL with extensions for time-series applications | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | JDBC ODBC OLE DB | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET HTTP API JDBC ODBC | JDBC RESTful HTTP API | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C++ Fortran Java Lua Perl Python R | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C C# C++ Delphi Java JavaScript (Node.js) Perl PHP Python Ruby | C C# C++ Go Java JavaScript (Node.js) PHP Python Rust | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | Yes, possible languages: KQL, Python, R | yes | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes, in C/C++, Java, .Net or Perl | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | yes | yes | yes, via alarm monitoring | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding Implicit feature of the cloud service | Sharding | partitioning by range, list and (since PostgreSQL 11) by hash | none | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | Source-replica replication Database mirroring | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | Spark connector (open source): github.com/Azure/azure-kusto-spark | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | yes | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | ACID | ACID | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | 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 | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Azure Active Directory Authentication | Users with fine-grained authorization concept | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Microsoft Azure Data Explorer | Netezza Also called PureData System for Analytics by IBM | PostgreSQL | SAP SQL Anywhere formerly called Adaptive Server Anywhere | TDengine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | TDengine™ is a next generation data historian purpose-built for Industry 4.0 and... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | High Performance at any Scale: TDengine is purpose-built for handling massive industrial... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | TDengine OSS is an open source, cloud native time series database. It includes built-in... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Seamless Data Integration from MQTT and InfluxDB to TDengine Solving Long Query Performance Bottlenecks What Is Predictive Maintenance? Can Typical Time-Series Databases Replace Data Historians? TDengine 3.3.0.0 Release Notes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Microsoft Azure Data Explorer | Netezza Also called PureData System for Analytics by IBM | PostgreSQL | SAP SQL Anywhere formerly called Adaptive Server Anywhere | TDengine | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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