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DBMS > Datomic vs. LevelDB vs. PouchDB vs. Splice Machine

System Properties Comparison Datomic vs. LevelDB vs. PouchDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonLevelDB  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesJavaScript DBMS with an API inspired by CouchDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score2.28
Rank#115  Overall
#21  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comgithub.com/­google/­leveldbpouchdb.comsplicemachine.com
Technical documentationdocs.datomic.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdpouchdb.com/­guidessplicemachine.com/­how-it-works
DeveloperCognitectGoogleApache Software FoundationSplice Machine
Initial release2012201120122014
Current release1.0.6735, June 20231.23, February 20217.1.1, June 20193.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoBSDOpen SourceOpen 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 languageJava, ClojureC++JavaScriptJava
Server operating systemsAll OS with a Java VMIllumos
Linux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyes
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 indexesyesnoyes infovia viewsyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsRESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoView functions in JavaScriptyes infoJava
TriggersBy using transaction functionsnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneSharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infowith automatic compression on writesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlnononoAccess rights for users, groups and roles according to SQL-standard

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More resources
DatomicLevelDBPouchDBSplice Machine
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