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DBMS > GridGain vs. LMDB vs. RavenDB vs. Spark SQL vs. Stardog

System Properties Comparison GridGain vs. LMDB vs. RavenDB vs. Spark SQL vs. Stardog

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonLMDB  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA high performant, light-weight, embedded key-value database libraryOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value store
Relational DBMS
Key-value storeDocument storeRelational DBMSGraph DBMS
RDF store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.gridgain.comwww.symas.com/­symas-embedded-database-lmdbravendb.netspark.apache.org/­sqlwww.stardog.com
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.lmdb.tech/­docravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperGridGain Systems, Inc.SymasHibernating RhinosApache Software FoundationStardog-Union
Initial release20072011201020142010
Current releaseGridGain 8.5.10.9.32, January 20245.4, July 20223.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetCC#ScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
Linux
Unix
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesschema-freeschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesnoyesyes
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 infoImport/export of XML data possible
Secondary indexesyesnoyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (RQL)SQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.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
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noyesnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes (cache interceptors and events)noyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)noneMulti-source replicationnoneMulti-source replication in HA-Cluster
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 in HA-Cluster
Foreign keys infoReferential integritynonononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID, Cluster-wide transaction availablenoACID
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.yesyesnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsnoAuthorization levels configured per client per databasenoAccess rights for users and roles

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More resources
GridGainLMDBRavenDBSpark SQLStardog
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