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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonatoti  Xexclude from comparisonKinetica  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.Fully vectorized database across both GPUs and CPUsA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMS
Time Series DBMS
Object oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitedruid.apache.orgatoti.iowww.kinetica.comwww.teradata.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.atoti.iodocs.kinetica.comdocs.teradata.com
DeveloperApache Software Foundation and contributorsActiveViamKineticaTeradata
Initial release201220121984
Current release29.0.1, April 20247.1, August 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree versions availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, C++
Server operating systemsLinux
OS X
Unix
Linuxhosted
Linux
Data schemeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyes
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)SQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnoPythonuser defined functionsyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
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 methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.noyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
Apache DruidatotiKineticaTeradata
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