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DBMS > Apache Impala vs. Datomic vs. HEAVY.AI vs. Microsoft SQL Server vs. TinkerGraph

System Properties Comparison Apache Impala vs. Datomic vs. HEAVY.AI vs. Microsoft SQL Server vs. TinkerGraph

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareMicrosofts flagship relational DBMSA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSGraph DBMS
Secondary database modelsDocument storeSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score821.56
Rank#3  Overall
#3  Relational DBMS
Score0.13
Rank#345  Overall
#35  Graph DBMS
Websiteimpala.apache.orgwww.datomic.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.microsoft.com/­en-us/­sql-servertinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.heavy.ailearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectHEAVY.AI, Inc.Microsoft
Initial release20132012201619892009
Current release4.1.0, June 20221.0.7075, December 20235.10, January 2022SQL Server 2022, November 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freeOpen Source infoApache Version 2; enterprise edition availablecommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureC++ and CUDAC++Java
Server operating systemsLinuxAll OS with a Java VMLinuxLinux
Windows
Data schemeyesyesyesyesschema-free
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.nononoyesno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
All languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Groovy
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction FunctionsnoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
TriggersnoBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersSharding infoRound robintables can be distributed across several files (horizontal partitioning); sharding through federationnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersMulti-source replicationyes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynononoyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
Apache ImpalaDatomicHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft SQL ServerTinkerGraph
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