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DBMS > AgensGraph vs. Apache Impala vs. HEAVY.AI vs. Kinetica vs. Microsoft Azure SQL Database

System Properties Comparison AgensGraph vs. Apache Impala vs. HEAVY.AI vs. Kinetica vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonApache Impala  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAnalytic DBMS for HadoopA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMSSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Websitebitnine.net/­agensgraphimpala.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationbitnine.net/­documentationimpala.apache.org/­impala-docs.htmldocs.heavy.aidocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperBitnine Global Inc.Apache Software Foundation infoApache top-level project, originally developed by ClouderaHEAVY.AI, Inc.KineticaMicrosoft
Initial release20162013201620122010
Current release2.1, December 20184.1.0, June 20225.10, January 20227.1, August 2021V12
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2Open Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C++ and CUDAC, C++C++
Server operating systemsLinux
OS X
Windows
LinuxLinuxLinuxhosted
Data schemedepending on used data modelyesyesyesyes
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.nonononoyes
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsyes
APIs and other access methodsCypher Query Language
JDBC
JDBC
ODBC
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesC
Java
JavaScript
Python
All languages supporting JDBC/ODBCAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenouser defined functionsTransact SQL
Triggersnononoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replicationSource-replica replicationyes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
AgensGraphApache ImpalaHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaMicrosoft Azure SQL Database infoformerly SQL Azure
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