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DBMS > Apache Druid vs. Hive vs. Ignite vs. Teradata Aster

System Properties Comparison Apache Druid vs. Hive vs. Ignite vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHive  Xexclude from comparisonIgnite  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 datadata warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value store
Relational DBMS
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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitedruid.apache.orghive.apache.orgignite.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designcwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docs
DeveloperApache Software Foundation and contributorsApache Software Foundation infoinitially developed by FacebookApache Software FoundationTeradata
Initial release2012201220152005
Current release29.0.1, April 20243.1.3, April 2022Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, Java, .Net
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
OS X
Solaris
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesyesFlexible 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 dateyesyesyesyes
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.noyesyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)R packages
Triggersnonoyes (cache interceptors and events)no
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 enginesselectable replication factoryes (replicated cache)yes 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 infoquery execution via MapReduceyes (compute grid and hadoop accelerator)yes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
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.noyesno
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 rolesSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Apache DruidHiveIgniteTeradata Aster
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