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DBMS > Heroic vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. SWC-DB

System Properties Comparison Heroic vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. SWC-DB

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully vectorized database across both GPUs and CPUsElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerWidely used in-process key-value storeA high performance, scalable Wide Column DBMS
Primary database modelTime Series DBMSRelational 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 DBMS
Time Series DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitegithub.com/­spotify/­heroicwww.kinetica.comazure.microsoft.com/­services/­synapse-analyticswww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationspotify.github.io/­heroicdocs.kinetica.comdocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperSpotifyKineticaMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleAlex Kashirin
Initial release20142012201619942020
Current release7.1, August 202118.1.40, May 20200.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infocommercial license availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++C, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsLinuxhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Data schemeschema-freeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nononoyes infoonly with the Berkeley DB XML editionno
Secondary indexesyes infovia Elasticsearchyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyes infoSQL interfaced based on SQLite is availableSQL-like query language
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C#
Java
PHP
.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 proceduresnouser defined functionsTransact SQLnono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelyesno

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More resources
HeroicKineticaMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseOracle Berkeley DBSWC-DB infoSuper Wide Column Database
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