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DBMS > Hypertable vs. Interbase vs. RavenDB vs. Splice Machine vs. TerarkDB

System Properties Comparison Hypertable vs. Interbase vs. RavenDB vs. Splice Machine vs. TerarkDB

Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonInterbase  Xexclude from comparisonRavenDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTerarkDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopLight-weight proven RDBMS infooriginally from BorlandOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelWide column storeRelational DBMSDocument storeRelational DBMSKey-value store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitewww.embarcadero.com/­products/­interbaseravendb.netsplicemachine.comgithub.com/­bytedance/­terarkdb
Technical documentationdocs.embarcadero.com/­products/­interbaseravendb.net/­docssplicemachine.com/­how-it-worksbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperHypertable Inc.EmbarcaderoHibernating RhinosSplice MachineByteDance, originally Terark
Initial release20091984201020142016
Current release0.9.8.11, March 2016InterBase 2020, December 20195.4, July 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoAGPL 3.0, commercial license availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC#JavaC++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Android
iOS
Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesnoyesno
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.no infoexport as XML data possibleno
Secondary indexesrestricted infoonly exact value or prefix value scansyesyesyesno
SQL infoSupport of SQLnoyesSQL-like query language (RQL)yesno
APIs and other access methodsC++ API
Thrift
ADO.NET
JDBC
ODBC
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
C++ API
Java API
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnoyes infoInterbase procedure and trigger languageyesyes infoJavano
Triggersnoyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelInterbase Change ViewsMulti-source replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, Cluster-wide transaction availableACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyes, multi-version concurrency control (MVCC)yes
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.yesyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAuthorization levels configured per client per databaseAccess rights for users, groups and roles according to SQL-standardno

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More resources
HypertableInterbaseRavenDBSplice MachineTerarkDB
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