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DBMS > Blazegraph vs. GeoMesa vs. RavenDB vs. Spark SQL vs. Stardog

System Properties Comparison Blazegraph vs. GeoMesa vs. RavenDB vs. Spark SQL vs. Stardog

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGeoMesa  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Open 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 modelGraph DBMS
RDF store
Spatial DBMSDocument 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
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score0.78
Rank#213  Overall
#4  Spatial DBMS
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
Websiteblazegraph.comwww.geomesa.orgravendb.netspark.apache.org/­sqlwww.stardog.com
Technical documentationwiki.blazegraph.comwww.geomesa.org/­documentation/­stable/­user/­index.htmlravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperBlazegraphCCRi and othersHibernating RhinosApache Software FoundationStardog-Union
Initial release20062014201020142010
Current release2.1.5, March 20194.0.5, February 20245.4, July 20223.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Source infoApache License 2.0Open 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

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Implementation languageJavaScalaC#ScalaJava
Server operating systemsLinux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeschema-freeyesschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesnoyesyes
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.nonono infoImport/export of XML data possible
Secondary indexesyesyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-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 methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
.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 languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.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 proceduresyesnoyesnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnonoyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesdepending on storage layerMulti-source replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationdepending on storage layerDefault 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 integrityyes infoRelationships in Graphsnononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, 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.depending on storage layernoyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)yes infodepending on the DBMS used for storageAuthorization levels configured per client per databasenoAccess rights for users and roles

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More resources
BlazegraphGeoMesaRavenDBSpark SQLStardog
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