DBMS > Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere vs. Vertica
System Properties Comparison Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere vs. Vertica
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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 | Vertica OpenText™ Vertica™ 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 | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 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 | Spatial DBMS Time Series 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 | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.microsoft.com/en-us/azure/data-explorer | www.postgresql.org/docs | help.sap.com/docs/SAP_SQL_Anywhere | vertica.com/documentation | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Microsoft | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | SAP formerly Sybase | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2019 | 2000 | 1989 1989: Postgres, 1996: PostgreSQL | 1992 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | cloud service with continuous releases | 16.3, May 2024 | 17, July 2015 | 12.0.3, January 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | commercial | Open Source BSD | commercial | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | Fixed schema with schema-less datatypes (dynamic) | yes | yes | yes | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | yes | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 JDBCJavaScript (Node.js) Perl PHP Python Tcl | C C# C++ Delphi Java JavaScript (Node.js) Perl PHP Python Ruby | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | yes | yes | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | Spark connector (open source): github.com/Azure/azure-kusto-spark | yes | no | no | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID | 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 | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Microsoft Azure Data Explorer | Netezza Also called PureData System for Analytics by IBM | PostgreSQL | SAP SQL Anywhere formerly called Adaptive Server Anywhere | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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