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DBMS > Apache Druid vs. atoti vs. GridDB vs. Teradata

System Properties Comparison Apache Druid vs. atoti vs. GridDB vs. Teradata

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonatoti  Xexclude from comparisonGridDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Scalable in-memory time series database optimized for IoT and Big DataA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMS
Time Series DBMS
Object oriented DBMSTime Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series 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
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitedruid.apache.orgatoti.iogriddb.netwww.teradata.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.atoti.iodocs.griddb.netdocs.teradata.com
DeveloperApache Software Foundation and contributorsActiveViamToshiba CorporationTeradata
Initial release201220131984
Current release29.0.1, April 20245.1, August 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree versions 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 languageJavaJavaC++
Server operating systemsLinux
OS X
Unix
Linuxhosted
Linux
Data schemeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyes 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.nonoyes
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL for queryingMultidimensional Expressions (MDX)SQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL 2016 + extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnoPythonnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding, horizontal partitioningShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidatotiGridDBTeradata
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 DruidatotiGridDBTeradata
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