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DBMS > Apache Impala vs. Datomic vs. Elasticsearch vs. Quasardb vs. Spark SQL

System Properties Comparison Apache Impala vs. Datomic vs. Elasticsearch vs. Quasardb vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonElasticsearch  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA 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 metricDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSSearch engineTime Series DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.datomic.comwww.elastic.co/­elasticsearchquasar.aispark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectElasticquasardbApache Software Foundation
Initial release20132012201020092014
Current release4.1.0, June 20221.0.6735, June 20238.6, January 20233.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freeOpen Source infoElastic Licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureJavaC++Scala
Server operating systemsLinuxAll OS with a Java VMAll OS with a Java VMBSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binaryyes
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.nonononono
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infowith tagsno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJava API
RESTful HTTP/JSON API
HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyesnono
TriggersnoBy using transaction functionsyes infoby using the 'percolation' featurenono
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersyesSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoES-Hadoop Connectorwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoby using LevelDByes
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 developmentMemcached and Redis integrationyes infoTransient modeno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoCryptographically strong user authentication and audit trailno

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More resources
Apache ImpalaDatomicElasticsearchQuasardbSpark SQL
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