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DBMS > BigObject vs. GridGain vs. Netezza vs. Rockset vs. Teradata Aster

System Properties Comparison BigObject vs. GridGain vs. Netezza vs. Rockset vs. Teradata Aster

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonGridGain  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRockset  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.
DescriptionAnalytic DBMS for real-time computations and queriesGridGain is an in-memory computing platform, built on Apache IgniteData warehouse and analytics appliance part of IBM PureSystemsA scalable, reliable search and analytics service in the cloud, built on RocksDBPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Relational DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websitebigobject.iowww.gridgain.comwww.ibm.com/­products/­netezzarockset.com
Technical documentationdocs.bigobject.iowww.gridgain.com/­docs/­index.htmldocs.rockset.com
DeveloperBigObject, Inc.GridGain Systems, Inc.IBMRocksetTeradata
Initial release20152007200020192005
Current releaseGridGain 8.5.1
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Solaris
Windows
Linux infoincluded in appliancehostedLinux
Data schemeyesyesyesschema-freeFlexible 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 dateyesyesyesdynamic typingyes
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.noyesno infoingestion from XML files supportedyes infoin Aster File Store
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLyesRead-only SQL queries, including JOINsyes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
HTTP RESTADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresLuayes (compute grid and cache interceptors can be used instead)yesnoR packages
Triggersnoyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)Source-replica replicationyesyes 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)yesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoSecurity Hooks for custom implementationsUsers with fine-grained authorization conceptAccess rights for users and organizations can be defined via Rockset consolefine grained access rights according to SQL-standard

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More resources
BigObjectGridGainNetezza infoAlso called PureData System for Analytics by IBMRocksetTeradata Aster
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