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DBMS > GridGain vs. Microsoft Azure Table Storage vs. RavenDB vs. Spark SQL vs. Transbase

System Properties Comparison GridGain vs. Microsoft Azure Table Storage vs. RavenDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA Wide Column Store for rapid development using massive semi-structured datasetsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value store
Relational DBMS
Wide column storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.84
Rank#101  Overall
#18  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.gridgain.comazure.microsoft.com/­en-us/­services/­storage/­tablesravendb.netspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationwww.gridgain.com/­docs/­index.htmlravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperGridGain Systems, Inc.MicrosoftHibernating RhinosApache Software FoundationTransaction Software GmbH
Initial release20072012201020141987
Current releaseGridGain 8.5.15.4, July 20223.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC#ScalaC and C++
Server operating systemsLinux
OS X
Solaris
Windows
hostedLinux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.yesnonono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (RQL)SQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noyesnoyes
Triggersyes (cache interceptors and events)noyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACID, Cluster-wide transaction availablenoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonono
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights based on private key authentication or shared access signaturesAuthorization levels configured per client per databasenofine grained access rights according to SQL-standard

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More resources
GridGainMicrosoft Azure Table StorageRavenDBSpark SQLTransbase
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