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DBMS > HEAVY.AI vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SWC-DB

System Properties Comparison HEAVY.AI vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SWC-DB

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareMicrosofts flagship relational DBMSWidely used in-process key-value storeA high performance, scalable Wide Column DBMS
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Wide column store
Secondary database modelsSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score829.80
Rank#3  Overall
#3  Relational DBMS
Score2.52
Rank#114  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.01
Rank#387  Overall
#13  Wide column stores
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.microsoft.com/­en-us/­sql-serverwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.heavy.ailearn.microsoft.com/­en-US/­sql/­sql-serverdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperHEAVY.AI, Inc.MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleAlex Kashirin
Initial release2016198919942020
Current release5.10, January 2022SQL Server 2022, November 202218.1.40, May 20200.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercial inforestricted free version is availableOpen Source infocommercial license availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC++C, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsLinuxLinux
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesno
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.noyesyes infoonly with the Berkeley DB XML editionno
Secondary indexesnoyesyes
SQL infoSupport of SQLyesyesyes infoSQL interfaced based on SQLite is availableSQL-like query language
APIs and other access methodsJDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Proprietary protocol
Thrift
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++
Server-side scripts infoStored proceduresnoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javanono
Triggersnoyesyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robintables can be distributed across several files (horizontal partitioning); sharding through federationnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes, but depending on the SQL-Server EditionSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft SQL ServerOracle Berkeley DBSWC-DB infoSuper Wide Column Database
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