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DBMS > Apache Impala vs. Datomic vs. PouchDB vs. Splice Machine

System Properties Comparison Apache Impala vs. Datomic vs. PouchDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityJavaScript 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 DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteimpala.apache.orgwww.datomic.compouchdb.comsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.compouchdb.com/­guidessplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectApache Software FoundationSplice Machine
Initial release2013201220122014
Current release4.1.0, June 20221.0.7075, December 20237.1.1, June 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freeOpen 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 languageC++Java, ClojureJavaScriptJava
Server operating systemsLinuxAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesyes infovia viewsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction FunctionsView functions in JavaScriptyes infoJava
TriggersnoBy using transaction functionsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersSharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersMulti-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 methodsyes infoquery execution via MapReducenoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes 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.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaDatomicPouchDBSplice Machine
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