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DBMS > Apache Druid vs. GigaSpaces vs. GridDB vs. Teradata Aster

System Properties Comparison Apache Druid vs. GigaSpaces vs. GridDB vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGridDB  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh 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 DataPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Websitedruid.apache.orgwww.gigaspaces.comgriddb.net
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.net
DeveloperApache Software Foundation and contributorsGigaspaces TechnologiesToshiba CorporationTeradata
Initial release2012200020132005
Current release29.0.1, April 202415.5, September 20205.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetC++
Server operating systemsLinux
OS X
Unix
Linux
macOS
Solaris
Windows
LinuxLinux
Data schemeyes infoschema-less columns are supportedschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nono infoXML can be used for describing objects metadatanoyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyesnoR packages
Triggersnoyes, event driven architectureyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelACID
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.noyesyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemRole-based access controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidGigaSpacesGridDBTeradata Aster
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 DruidGigaSpacesGridDBTeradata Aster
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