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DBMS > Drizzle vs. Hypertable vs. RavenDB vs. Splice Machine

System Properties Comparison Drizzle vs. Hypertable vs. RavenDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHypertable  Xexclude from comparisonRavenDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.An 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 Spark
Primary database modelRelational DBMSWide column storeDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.47
Rank#95  Overall
#16  Document stores
Score0.54
Rank#257  Overall
#118  Relational DBMS
Websiteravendb.netsplicemachine.com
Technical documentationravendb.net/­docssplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerHypertable Inc.Hibernating RhinosSplice Machine
Initial release2008200920102014
Current release7.2.4, September 20120.9.8.11, March 20165.4, July 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoGNU version 3. Commercial license availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C#Java
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like query language (RQL)yes
APIs and other access methodsJDBCC++ 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
Supported programming languagesC
C++
Java
PHP
C++
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
Server-side scripts infoStored proceduresnonoyesyes infoJava
Triggersno infohooks for callbacks inside the server can be used.noyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor on file system levelMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesYes, via Full Spark Integration
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 Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAuthorization levels configured per client per databaseAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleHypertableRavenDBSplice Machine
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