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DBMS > Elasticsearch vs. GridDB vs. Impala vs. Spark SQL

System Properties Comparison Elasticsearch vs. GridDB vs. Impala vs. Spark SQL

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGridDB  Xexclude from comparisonImpala  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA 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 DataAnalytic DBMS for HadoopSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSearch engineTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score150.32
Rank#7  Overall
#1  Search engines
Score1.80
Rank#143  Overall
#11  Time Series DBMS
Score17.92
Rank#39  Overall
#24  Relational DBMS
Score21.90
Rank#36  Overall
#22  Relational DBMS
Websitewww.elastic.co/­elasticsearchgriddb.netwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlspark.apache.org/­sql
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.griddb.netdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperElasticToshiba CorporationClouderaApache Software Foundation
Initial release2010201320132014
Current release7.8.0, June 20205.1, August 20224.1.0, June 20223.3.0 ( 2.13), June 2022
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open 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.
Implementation languageJavaC++C++Scala
Server operating systemsAll OS with a Java VMLinuxLinuxLinux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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 indexesyes infoAll search fields are automatically indexedyesyesno
SQL infoSupport of SQLSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBCJava
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyes infouser defined functions and integration of map-reduceno
Triggersyes infoby using the 'percolation' featureyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectorConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 containersEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnono
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.Memcached and Redis integrationyesnono
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno
More information provided by the system vendor
ElasticsearchGridDBImpalaSpark SQL
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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More resources
ElasticsearchGridDBImpalaSpark SQL
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