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DBMS > Blazegraph vs. Google Cloud Datastore vs. Riak TS vs. Warp 10

System Properties Comparison Blazegraph vs. Google Cloud Datastore vs. Riak TS vs. Warp 10

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak TS  Xexclude from comparisonWarp 10  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelGraph DBMS
RDF store
Document storeTime Series DBMSTime 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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websiteblazegraph.comcloud.google.com/­datastorewww.warp10.io
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docswww.tiot.jp/­riak-docs/­riak/­ts/­latestwww.warp10.io/­content/­02_Getting_started
DeveloperBlazegraphGoogleOpen Source, formerly Basho TechnologiesSenX
Initial release2006200820152015
Current release2.1.5, March 20193.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialOpen SourceOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangJava
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes, details herenoyes
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 indexesyesyesrestrictedno
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)yes, limitedno
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
HTTP API
Jupyter
WebSocket
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyesusing Google App EngineErlangyes infoWarpScript
TriggersnoCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factorselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate 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.Eventual ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsno infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
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.noyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
BlazegraphGoogle Cloud DatastoreRiak TSWarp 10
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