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DBMS > Apache Impala vs. CouchDB vs. Datomic vs. Spark SQL

System Properties Comparison Apache Impala vs. CouchDB vs. Datomic vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonDatomic  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score10.26
Rank#45  Overall
#7  Document stores
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgcouchdb.apache.orgwww.datomic.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stabledocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerCognitectApache Software Foundation
Initial release2013200520122014
Current release4.1.0, June 20223.3.3, December 20231.0.6735, June 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2commercial infolimited edition freeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangJava, ClojureScala
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononono
Secondary indexesyesyes infovia viewsyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP/JSON APIRESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Clojure
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceView functions in JavaScriptyes infoTransaction Functionsno
TriggersnoyesBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0none infoBut extensive use of caching in the application peersyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databasenono

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Apache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"DatomicSpark SQL
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