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DBMS > Blazegraph vs. Google Cloud Datastore vs. Teradata vs. Warp 10

System Properties Comparison Blazegraph vs. Google Cloud Datastore vs. Teradata vs. Warp 10

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTeradata  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 PlatformA hybrid cloud data analytics software platform (Teradata Vantage)TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelGraph DBMS
RDF store
Document storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time 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
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websiteblazegraph.comcloud.google.com/­datastorewww.teradata.comwww.warp10.io
Technical documentationwiki.blazegraph.comcloud.google.com/­datastore/­docsdocs.teradata.comwww.warp10.io/­content/­02_Getting_started
DeveloperBlazegraphGoogleTeradataSenX
Initial release2006200819842015
Current release2.1.5, March 2019Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoextended commercial license availablecommercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinux
OS X
Windows
hostedhosted
Linux
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes, details hereyesyes
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.noyesno
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexno
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language (GQL)yes infoSQL 2016 + extensionsno
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyesusing Google App Engineyes infoUDFs, stored procedures, table functions in parallelyes infoWarpScript
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoHashingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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.Immediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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.noyesyes
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)fine grained access rights according to SQL-standardMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
BlazegraphGoogle Cloud DatastoreTeradataWarp 10
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