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DBMS > Drizzle vs. HEAVY.AI vs. Kinetica vs. Microsoft Access vs. Microsoft Azure Synapse Analytics

System Properties Comparison Drizzle vs. HEAVY.AI vs. Kinetica vs. Microsoft Access vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.heavy.aidocs.kinetica.comdeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­azure/­synapse-analytics
DeveloperDrizzle project, originally started by Brian AkerHEAVY.AI, Inc.KineticaMicrosoftMicrosoft
Initial release20082016201219922016
Current release7.2.4, September 20125.10, January 20227.1, August 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++ and CUDAC, C++C++C++
Server operating systemsFreeBSD
Linux
OS X
LinuxLinuxWindows infoNot a real database server, but making use of DLLshosted
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like DML and DDL statementsyes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
PHP
Server-side scripts infoStored proceduresnonouser defined functionsyes infosince Access 2010 using the ACE-engineTransact SQL
Triggersno infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinShardingnoneSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users and roles on table levelno infoa simple user-level security was built in till version Access 2003yes

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More resources
DrizzleHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMicrosoft AccessMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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