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DBMS > Blazegraph vs. IRONdb vs. LeanXcale vs. Microsoft Azure Table Storage vs. Splice Machine

System Properties Comparison Blazegraph vs. IRONdb vs. LeanXcale vs. Microsoft Azure Table Storage vs. Splice Machine

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonIRONdb  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Time Series DBMSKey-value store
Relational DBMS
Wide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteblazegraph.comwww.circonus.com/solutions/time-series-database/www.leanxcale.comazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationwiki.blazegraph.comdocs.circonus.com/irondb/category/getting-startedsplicemachine.com/­how-it-works
DeveloperBlazegraphCirconus LLC.LeanXcaleMicrosoftSplice Machine
Initial release20062017201520122014
Current release2.1.5, March 2019V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes infotext, numeric, histogramsyesyes
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.nono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (Circonus Analytics Query Language: CAQL)yes infothrough Apache Derbynoyes
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
HTTP APIJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
Java
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyes, in Luanoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesconfigurable replication factor, datacenter awareyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.noyesnoyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)noAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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More resources
BlazegraphIRONdbLeanXcaleMicrosoft Azure Table StorageSplice Machine
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