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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCockroachDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A 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
Score6.15
Rank#55  Overall
#33  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.cockroachlabs.comwww.elastic.co/­elasticsearchquasar.aispark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlwww.cockroachlabs.com/­docswww.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 ClouderaCockroach LabsElasticquasardbApache Software Foundation
Initial release20132015201020092014
Current release4.1.0, June 202223.1.1, May 20238.6, January 20233.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0, commercial license availableOpen 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++GoJavaC++Scala
Server operating systemsLinuxLinux
macOS
Windows
All OS with a Java VMBSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesdynamic schemaschema-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 statementsyes, wire compatible with PostgreSQLSQL-like query languageSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBCJava API
RESTful HTTP/JSON API
HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.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-reducenoyesnono
Triggersnonoyes infoby using the 'percolation' featurenono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using RAFTyesSource-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 integritynoyesnonono
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 persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoMemcached and Redis integrationyes infoTransient modeno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlCryptographically strong user authentication and audit trailno

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More resources
Apache ImpalaCockroachDBElasticsearchQuasardbSpark SQL
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