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DBMS > Apache Druid vs. Apache Impala vs. GigaSpaces vs. GridDB vs. RocksDB

System Properties Comparison Apache Druid vs. Apache Impala vs. GigaSpaces vs. GridDB vs. RocksDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridDB  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big DataEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSKey-value store
Secondary database modelsDocument storeGraph DBMS
Search engine
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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Websitedruid.apache.orgimpala.apache.orgwww.gigaspaces.comgriddb.netrocksdb.org
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.netgithub.com/­facebook/­rocksdb/­wiki
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaGigaspaces TechnologiesToshiba CorporationFacebook, Inc.
Initial release20122013200020132013
Current release29.0.1, April 20244.1.0, June 202215.5, September 20205.1, August 20228.11.4, April 2024
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoBSD
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 languageJavaC++Java, C++, .NetC++C++
Server operating systemsLinux
OS X
Unix
LinuxLinux
macOS
Solaris
Windows
LinuxLinux
Data schemeyes infoschema-less columns are supportedyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes 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.nonono infoXML can be used for describing objects metadatanono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
C++ API
Java API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesnono
Triggersnonoyes, event driven architectureyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at container levelyes
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.nonoyesyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache DruidApache ImpalaGigaSpacesGridDBRocksDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache DruidApache ImpalaGigaSpacesGridDBRocksDB
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