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DBMS > Blazegraph vs. EXASOL vs. Google Cloud Datastore vs. IRONdb

System Properties Comparison Blazegraph vs. EXASOL vs. Google Cloud Datastore vs. IRONdb

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument storeTime 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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websiteblazegraph.comwww.exasol.comcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/
Technical documentationwiki.blazegraph.comwww.exasol.com/­resourcescloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperBlazegraphExasolGoogleCirconus LLC.
Initial release2006200020082017
Current release2.1.5, March 2019V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++
Server operating systemsLinux
OS X
Windows
hostedLinux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyes, details hereyes infotext, numeric, histograms
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 indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageyesSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyesuser defined functionsusing Google App Engineyes, in Lua
TriggersnoyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyes infoRelationships in Graphsyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.yesnono
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
BlazegraphEXASOLGoogle Cloud DatastoreIRONdb
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