DBMS > Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere vs. Titan
System Properties Comparison Microsoft Azure Data Explorer vs. Netezza vs. PostgreSQL vs. SAP SQL Anywhere vs. Titan
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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 | Titan Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Titan is a Graph DBMS optimized for distributed clusters. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Graph 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 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 | 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/thinkaurelius/titan | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.microsoft.com/en-us/azure/data-explorer | www.postgresql.org/docs | help.sap.com/docs/SAP_SQL_Anywhere | github.com/thinkaurelius/titan/wiki | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Microsoft | IBM | PostgreSQL Global Development Group www.postgresql.org/developer | SAP formerly Sybase | Aurelius, owned by DataStax | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2019 | 2000 | 1989 1989: Postgres, 1996: PostgreSQL | 1992 | 2012 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | cloud service with continuous releases | 16.3, May 2024 | 17, July 2015 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | commercial | Open Source BSD | commercial | Open Source Apache license, version 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Implementation language | C | Java | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 OS X Unix 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | all fields are automatically indexed | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Java API TinkerPop Blueprints TinkerPop Frames TinkerPop Gremlin TinkerPop Rexster | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Clojure Java Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | no | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | yes via pluggable storage backends | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | yes via Faunus, a graph analytics engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | Eventual Consistency Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | no | yes | yes | yes Relationships in graph | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | User authentification and security via Rexster Graph Server | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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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 | Titan | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | Graph DBMS increased their popularity by 500% within the last 2 years Graph DBMSs are gaining in popularity faster than any other database category 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 IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS AWS and IBM Netezza come out in support of Iceberg in table format face-off Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services IBM Brings Back a Netezza, Attacks Yellowbrick U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza provided by Google News How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ... EDB unveils EDB Postgres AI Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need Why PostgreSQL Is the Bedrock for the Future of Data General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News SAP vulnerabilities Let Attacker Inject OS Commands—Patch Now! SAP Again Named a Leader in 2021 Gartner® Magic Quadrant™ for Cloud Database Management Systems Rimini Street expands support beyond SAP and Oracle Securing SAP with AWS Network Firewall: Part 2 – Managed Rules | Amazon Web Services Rimini Street to offer database, security services provided by Google News Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services JanusGraph Picks Up Where TitanDB Left Off 5 Q's with Graph Database Expert Marko Rodriguez – Center for Data Innovation DSE Graph review: Graph database does double duty provided by Google News | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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