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DBMS > Apache Impala vs. Elasticsearch vs. PostgreSQL vs. Spark SQL

System Properties Comparison Apache Impala vs. Elasticsearch vs. PostgreSQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score134.78
Rank#7  Overall
#1  Search engines
Score645.05
Rank#4  Overall
#4  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchwww.postgresql.orgspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticPostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release201320101989 info1989: Postgres, 1996: PostgreSQL2014
Current release4.1.0, June 20228.6, January 202316.2, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic LicenseOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageC++JavaCScala
Server operating systemsLinuxAll OS with a Java VMFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnoyes infoby using the 'percolation' featureyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noMemcached and Redis integrationnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardno

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More resources
Apache ImpalaElasticsearchPostgreSQLSpark SQL
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