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DBMS > Bangdb vs. GeoMesa vs. Microsoft Azure Table Storage vs. Splice Machine

System Properties Comparison Bangdb vs. GeoMesa vs. Microsoft Azure Table Storage vs. Splice Machine

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGeoMesa  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Spatial DBMSWide column storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitebangdb.comwww.geomesa.orgazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationdocs.bangdb.comwww.geomesa.org/­documentation/­stable/­user/­index.htmlsplicemachine.com/­how-it-works
DeveloperSachin Sinha, BangDBCCRi and othersMicrosoftSplice Machine
Initial release2012201420122014
Current releaseBangDB 2.0, October 20214.0.5, February 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache License 2.0commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaJava
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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 indexesyes infosecondary, composite, nested, reverse, geospatialyesnoyes
SQL infoSupport of SQLSQL like support with command line toolnonoyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoJava
Triggersyes, Notifications (with Streaming only)nonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmdepending on storage layerSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)depending on storage layeryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglydepending on storage layerImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modedepending on storage layernoyes
User concepts infoAccess controlyes (enterprise version only)yes infodepending on the DBMS used for storageAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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More resources
BangdbGeoMesaMicrosoft Azure Table StorageSplice Machine
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