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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonPlanetScale  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable, distributed, serverless MySQL database platform built on top of VitessJavaScript 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 storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteimpala.apache.orgplanetscale.compouchdb.comsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlplanetscale.com/­docspouchdb.com/­guidessplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPlanetScaleApache Software FoundationSplice Machine
Initial release2013202020122014
Current release4.1.0, June 20227.1.1, June 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen SourceOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoJavaScriptJava
Server operating systemsLinuxDocker
Linux
macOS
server-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.nono
Secondary indexesyesyesyes infovia viewsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsnoyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoproprietary syntaxView functions in JavaScriptyes infoJava
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infonot for MyISAM storage enginenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at shard levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes 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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUsers with fine-grained authorization concept infono user groups or rolesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaPlanetScalePouchDBSplice Machine
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