DBMS > HEAVY.AI vs. Kinetica vs. Microsoft Azure Data Explorer vs. NuoDB vs. PostgreSQL
System Properties Comparison HEAVY.AI vs. Kinetica vs. Microsoft Azure Data Explorer vs. NuoDB vs. PostgreSQL
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Name | HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 Xexclude from comparison | Kinetica Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | NuoDB Xexclude from comparison | PostgreSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware | Fully vectorized database across both GPUs and CPUs | Fully managed big data interactive analytics platform | NuoDB is a webscale distributed database that supports SQL and ACID transactions | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | 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 | Spatial DBMS | Spatial DBMS Time Series 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 Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | github.com/heavyai/heavydb www.heavy.ai | www.kinetica.com | azure.microsoft.com/services/data-explorer | www.3ds.com/nuodb-distributed-sql-database | www.postgresql.org | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.heavy.ai | docs.kinetica.com | docs.microsoft.com/en-us/azure/data-explorer | doc.nuodb.com | www.postgresql.org/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | HEAVY.AI, Inc. | Kinetica | Microsoft | Dassault Systèmes originally NuoDB, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2016 | 2012 | 2019 | 2013 | 1989 1989: Postgres, 1996: PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.10, January 2022 | 7.1, August 2021 | cloud service with continuous releases | 16.3, May 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2; enterprise edition available | commercial | commercial | commercial limited edition free | Open Source BSD | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | C++ and CUDA | C, C++ | C++ | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux | Linux | hosted | hosted Amazon EC2, Windows Azure, SoftLayer Linux OS X Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | 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 | no | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | no | yes | all fields are automatically indexed | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | SQL-like DML and DDL statements | Kusto Query Language (KQL), SQL subset | yes | yes standard with numerous extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | JDBC ODBC Thrift Vega | JDBC ODBC RESTful HTTP API | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | ADO.NET JDBC ODBC | ADO.NET JDBC native C library ODBC streaming API for large objects | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | All languages supporting JDBC/ODBC/Thrift Python | C++ Java JavaScript (Node.js) Python | .Net Go Java JavaScript (Node.js) PowerShell Python R | .Net C C++ Go Java JavaScript JavaScript (Node.js) PHP Python Ruby | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | user defined functions | Yes, possible languages: KQL, Python, R | Java, SQL | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes triggers when inserted values for one or more columns fall within a specified range | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding Round robin | Sharding | Sharding Implicit feature of the cloud service | data is dynamically stored/cached on the nodes where it is read/written | 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 | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | yes Managed transparently by NuoDB | Source-replica replication other methods possible by using 3rd party extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | 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 | Immediate Consistency or Eventual Consistency depending on configuration | Eventual Consistency Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | no | no | ACID tunable commit protocol | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes MVCC | 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. | yes | yes GPU vRAM or System RAM | no | yes Temporary table | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | Access rights for users and roles on table level | Azure Active Directory Authentication | Standard SQL roles/ privileges, Administrative Users | fine grained access rights according to SQL-standard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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HEAVY.AI Formerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022 | Kinetica | Microsoft Azure Data Explorer | NuoDB | PostgreSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Meet some database management systems you are likely to hear more about in the future | 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 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 OmniSci Gets HEAVY New Name and New CEO The insideBIGDATA IMPACT 50 List for Q4 2023 provided by Google News Kinetica Delivers Real-Time Vector Similarity Search Kinetica Elevates RAG with Fast Access to Real-Time Data Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise Kinetica Delivers Real-Time Vector Similarity Search 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 Dassault Systèmes Announces the Acquisition of NuoDB, a Cloud-Native Distributed SQL Database Leader Deploy the NuoDB Database in Docker Containers NuoDB set to improve distributed SQL performance Big Data Product Watch 1/31/17: No-Cost NuoDB, GPU Analytics, Cloud Object Storage, More -- ADTmag Dassault Systèmes to acquire Cambridge database startup - Boston Business Journal provided by Google News Enterprise DB begins rolling AI features into PostgreSQL Deep PostgreSQL Thoughts: Valuing Currency EDB unveils EDB Postgres AI How to Import CSV Data Into PostgreSQL Using Spring Boot Batch Nutanix and EDB enhance PostgreSQL for enterprise apps provided by Google News |
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