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DBMS > Blazegraph vs. Drizzle vs. FatDB vs. Google Cloud Datastore

System Properties Comparison Blazegraph vs. Drizzle vs. FatDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelGraph DBMS
RDF store
Relational DBMSDocument store
Key-value store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#217  Overall
#19  Graph DBMS
#8  RDF stores
Score4.13
Rank#71  Overall
#12  Document stores
Websiteblazegraph.comcloud.google.com/­datastore
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docs
DeveloperBlazegraphDrizzle project, originally started by Brian AkerFatCloudGoogle
Initial release2006200820122008
Current release2.1.5, March 20197.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
OS X
Windowshosted
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyesyes, details here
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.no
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languageyes infowith proprietary extensionsno infoVia inetgration in SQL ServerSQL-like query language (GQL)
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C
C++
Java
PHP
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoyes infovia applicationsusing Google App Engine
Triggersnono infohooks for callbacks inside the server can be used.yes infovia applicationsCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate 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.
Foreign keys infoReferential integrityyes infoRelationships in Graphsyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.no
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Pluggable authentication mechanisms infoe.g. LDAP, HTTPno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
BlazegraphDrizzleFatDBGoogle Cloud Datastore
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