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DBMS > Blazegraph vs. InfinityDB vs. IRONdb vs. Transbase

System Properties Comparison Blazegraph vs. InfinityDB vs. IRONdb vs. Transbase

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonTransbase  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 Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelGraph DBMS
RDF store
Key-value storeTime Series DBMSRelational 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
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteblazegraph.comboilerbay.comwww.circonus.com/solutions/time-series-database/www.transaction.de/­en/­products/­transbase.html
Technical documentationwiki.blazegraph.comboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-startedwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperBlazegraphBoiler Bay Inc.Circonus LLC.Transaction Software GmbH
Initial release2006200220171987
Current release2.1.5, March 20194.0V0.10.20, January 2018Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialcommercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++C and C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinuxFreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsyes
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
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilitynoyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like query language (Circonus Analytics Query Language: CAQL)yes
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Java.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesnoyes, in Luayes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneconfigurable replication factor, datacenter awareSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsno infomanual creation possible, using inversions based on multi-value capabilitynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)nonofine grained access rights according to SQL-standard

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More resources
BlazegraphInfinityDBIRONdbTransbase
Recent citations in the news

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

Representation Learning on RDF* and LPG Knowledge Graphs
24 September 2020, Towards Data Science

Faster with GPUs: 5 turbocharged databases
26 September 2016, InfoWorld

provided by Google News

Application observability firm Apica buys telemetry data startup Circonus and adds more funding
21 February 2024, SiliconANGLE News

Apica Acquires Telemetry Data Management Pioneer Circonus And Lands New Funding
22 February 2024, Datanami

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News



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