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

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

Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonRavenDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTerarkDB  Xexclude from comparisonVelocityDB  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 HadoopOpen 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 MongoDBA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelWide column storeDocument storeRelational DBMSKey-value storeGraph DBMS
Object oriented DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websiteravendb.netsplicemachine.comgithub.com/­bytedance/­terarkdbvelocitydb.com
Technical documentationravendb.net/­docssplicemachine.com/­how-it-worksbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcvelocitydb.com/­UserGuide
DeveloperHypertable Inc.Hibernating RhinosSplice MachineByteDance, originally TerarkVelocityDB Inc
Initial release20092010201420162011
Current release0.9.8.11, March 20165.4, July 20223.1, March 20217.x
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoAGPL 3.0, commercial license availablecommercial inforestricted open source version availablecommercial
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++C#JavaC++C#
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Solaris
Windows
Any that supports .NET
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenonoyesnoyes
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.nono
Secondary indexesrestricted infoonly exact value or prefix value scansyesyesnoyes
SQL infoSupport of SQLnoSQL-like query language (RQL)yesnono
APIs and other access methodsC++ API
Thrift
.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
.Net
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
.Net
Server-side scripts infoStored proceduresnoyesyes infoJavanono
TriggersnoyesyesnoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar PartitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelMulti-source replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID, Cluster-wide transaction availableACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
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 controlnoAuthorization levels configured per client per databaseAccess rights for users, groups and roles according to SQL-standardnoBased on Windows Authentication

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More resources
HypertableRavenDBSplice MachineTerarkDBVelocityDB
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