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DBMS > Apache Druid vs. GridGain vs. HEAVY.AI vs. Teradata Aster

System Properties Comparison Apache Druid vs. GridGain vs. HEAVY.AI vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridGain  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  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 dataGridGain is an in-memory computing platform, built on Apache IgniteA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwarePlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial 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
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score2.10
Rank#126  Overall
#61  Relational DBMS
Websitedruid.apache.orgwww.gridgain.comgithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­index.htmldocs.heavy.ai
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.HEAVY.AI, Inc.Teradata
Initial release2012200720162005
Current release29.0.1, April 2024GridGain 8.5.15.10, January 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2; enterprise edition 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++ and CUDA
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
LinuxLinux
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.noyesnoyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingANSI-99 for query and DML statements, subset of DDLyesyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)noR packages
Triggersnoyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes (replicated cache)Multi-source 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 (compute grid and hadoop accelerator)noyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 datanoACIDnoACID
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 systemSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache DruidGridGainHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Teradata Aster
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