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DBMS > Apache Druid vs. BoltDB vs. Elasticsearch vs. GridDB vs. Oracle Berkeley DB

System Properties Comparison Apache Druid vs. BoltDB vs. Elasticsearch vs. GridDB vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBoltDB  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn embedded key-value store for Go.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 metricScalable in-memory time series database optimized for IoT and Big DataWidely used in-process key-value store
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeSearch engineTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.74
Rank#220  Overall
#31  Key-value stores
Score135.35
Rank#7  Overall
#1  Search engines
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitedruid.apache.orggithub.com/­boltdb/­boltwww.elastic.co/­elasticsearchgriddb.netwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdruid.apache.org/­docs/­latest/­designwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.griddb.netdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software Foundation and contributorsElasticToshiba CorporationOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20122013201020131994
Current release29.0.1, April 20248.6, January 20235.1, August 202218.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoMIT LicenseOpen Source infoElastic LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJavaC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsLinux
OS X
Unix
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyes infoschema-less columns are supportedschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.nonononoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesnoyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLSQL for queryingnoSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresnonoyesnono
Triggersnonoyes infoby using the 'percolation' featureyesyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoES-Hadoop ConnectorConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual 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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 integrationyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache DruidBoltDBElasticsearchGridDBOracle Berkeley DB
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
Apache DruidBoltDBElasticsearchGridDBOracle Berkeley DB
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