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DBMS > Hypertable vs. Splice Machine

System Properties Comparison Hypertable vs. Splice Machine

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonSplice Machine  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 SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.54
Rank#265  Overall
#120  Relational DBMS
Websitesplicemachine.com
Technical documentationsplicemachine.com/­how-it-works
DeveloperHypertable Inc.Splice Machine
Initial release20092014
Current release0.9.8.11, March 20163.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or datenoyes
Secondary indexesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnoyes
APIs and other access methodsC++ API
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standard

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HypertableSplice Machine
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