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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCockroachDB  Xexclude from comparisonDrizzle  Xexclude from comparisonElasticsearch  Xexclude from comparisonSpark SQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.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 metricSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engineRelational 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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgwww.cockroachlabs.comwww.elastic.co/­elasticsearchspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmlwww.cockroachlabs.com/­docswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCockroach LabsDrizzle project, originally started by Brian AkerElasticApache Software Foundation
Initial release20132015200820102014
Current release4.1.0, June 202223.1.1, May 20237.2.4, September 20128.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0, commercial license availableOpen Source infoGNU GPLOpen Source infoElastic LicenseOpen 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++GoC++JavaScala
Server operating systemsLinuxLinux
macOS
Windows
FreeBSD
Linux
OS X
All OS with a Java VMLinux
OS X
Windows
Data schemeyesdynamic schemayesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes, wire compatible with PostgreSQLyes infowith proprietary extensionsSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBCJDBCJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C
C++
Java
PHP
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyesno
Triggersnonono infohooks for callbacks inside the server can be used.yes infoby using the 'percolation' featureno
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 RAFTShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using RAFTMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoES-Hadoop Connector
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, all
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoMemcached and Redis integrationno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno

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More resources
Apache ImpalaCockroachDBDrizzleElasticsearchSpark SQL
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