DBMS > Elasticsearch vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. PostgreSQL
System Properties Comparison Elasticsearch vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. PostgreSQL
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Name | Elasticsearch Xexclude from comparison | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Postgres-XL Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric | A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware | Fully managed big data interactive analytics platform | Based on PostgreSQL enhanced with MPP and write-scale-out cluster features | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Search engine | 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 Vector DBMS | 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 engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Document store Spatial DBMS | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.elastic.co/elasticsearch | github.com/heavyai/heavydb www.heavy.ai | azure.microsoft.com/services/data-explorer | www.postgres-xl.org | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | www.elastic.co/guide/en/elasticsearch/reference/current/index.html | docs.heavy.ai | docs.microsoft.com/en-us/azure/data-explorer | www.postgres-xl.org/documentation | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Elastic | HEAVY.AI, Inc. | Microsoft | PostgreSQL Global Development Group www.postgresql.org/developer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2010 | 2016 | 2019 | 2014 since 2012, originally named StormDB | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 8.6, January 2023 | 5.10, January 2022 | cloud service with continuous releases | 10 R1, October 2018 | 16.2, February 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Elastic License | Open Source Apache Version 2; enterprise edition available | commercial | Open Source Mozilla public license | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Java | C++ and CUDA | C | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All OS with a Java VM | Linux | hosted | Linux macOS | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free Flexible type definitions. Once a type is defined, it is persistent | 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 XML type, but no XML query functionality | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes All search fields are automatically indexed | no | all fields are automatically indexed | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like query language | yes | Kusto Query Language (KQL), SQL subset | yes distributed, parallel query execution | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Java API RESTful HTTP/JSON API | JDBC ODBC Thrift Vega | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net Groovy Community Contributed Clients Java JavaScript Perl PHP Python Ruby | All languages supporting JDBC/ODBC/Thrift Python | .Net Go Java JavaScript (Node.js) PowerShell Python R | .Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | Yes, possible languages: KQL, Python, R | user defined functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes by using the 'percolation' feature | 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 Round robin | Sharding Implicit feature of the cloud service | horizontal partitioning | partitioning by range, list and (since PostgreSQL 11) by hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes | Multi-source replication | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Source-replica replication other methods possible by using 3rd party extensions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | ES-Hadoop Connector | no | Spark connector (open source): github.com/Azure/azure-kusto-spark | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all | Immediate 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 | no | no | no | ACID MVCC | 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. | Memcached and Redis integration | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Elasticsearch | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | Microsoft Azure Data Explorer | Postgres-XL | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2017 Elasticsearch moved into the top 10 most popular database management systems MySQL, PostgreSQL and Redis are the winners of the March ranking | 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 Monitoring PostgreSQL with Redgate Monitor Using Elasticsearch to Offload Search and Analytics from DynamoDB: Pros and Cons Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently The Total Economic Impact™️ of Elasticsearch 8 Powerful Alternatives to Elasticsearch Splunk vs Elasticsearch | A Comparison and How to Choose provided by Google News Big Data Analytics: A Game Changer for Infrastructure HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities Making the most of geospatial intelligence HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks The insideBIGDATA IMPACT 50 List for Q4 2023 provided by Google News General availability: Azure Data Explorer adds new geospatial capabilities | Azure updates Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog Azure Data Explorer: Log and telemetry analytics benchmark Introducing Microsoft Fabric: The data platform for the era of AI | Microsoft Azure Blog provided by Google News AGEDB Technology Launches PGTS - PostgreSQL Tech-Support Introducing OCI Database with PostgreSQL: Completing Our Cloud Database Suite for Every Need PostgreSQL Security Flaws Let Attackers Execute Code Automatically Generate Types for Your PostgreSQL Database General availability: Microsoft Entra ID integration with Azure Cosmos DB for PostgreSQL | Azure updates provided by Google News |
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