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DBMS > Apache Impala vs. Cubrid vs. Elasticsearch vs. GridDB

System Properties Comparison Apache Impala vs. Cubrid vs. Elasticsearch vs. GridDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCubrid  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA 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 metricScalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websiteimpala.apache.orgcubrid.com (korean)
cubrid.org (english)
www.elastic.co/­elasticsearchgriddb.net
Technical documentationimpala.apache.org/­impala-docs.htmlcubrid.org/­manualswww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.griddb.net
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCUBRID Corporation, CUBRID FoundationElasticToshiba Corporation
Initial release2013200820102013
Current release4.1.0, June 202211.0, January 20218.6, January 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoElastic LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++, JavaJavaC++
Server operating systemsLinuxLinux
Windows
All OS with a Java VMLinux
Data schemeyesyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyes
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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 indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava Stored Proceduresyesno
Triggersnoyesyes infoby using the 'percolation' featureyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoES-Hadoop ConnectorConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
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 within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID at container level
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.nonoMemcached and Redis integrationyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users can be defined per database
More information provided by the system vendor
Apache ImpalaCubridElasticsearchGridDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Apache ImpalaCubridElasticsearchGridDB
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