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DBMS > Blazegraph vs. Lovefield vs. SiteWhere vs. Splice Machine vs. WakandaDB

System Properties Comparison Blazegraph vs. Lovefield vs. SiteWhere vs. Splice Machine vs. WakandaDB

Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonLovefield  Xexclude from comparisonSiteWhere  Xexclude from comparisonSplice Machine  Xexclude from comparisonWakandaDB  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.Embeddable relational database for web apps written in pure JavaScriptM2M integration platform for persisting/querying time series dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelGraph DBMS
RDF store
Relational DBMSTime Series DBMSRelational DBMSObject oriented 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
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteblazegraph.comgoogle.github.io/­lovefieldgithub.com/­sitewhere/­sitewheresplicemachine.comwakanda.github.io
Technical documentationwiki.blazegraph.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsitewhere1.sitewhere.io/­index.htmlsplicemachine.com/­how-it-workswakanda.github.io/­doc
DeveloperBlazegraphGoogleSiteWhereSplice MachineWakanda SAS
Initial release20062014201020142012
Current release2.1.5, March 20192.1.12, February 20173.1, March 20212.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScriptJavaJavaC++, JavaScript
Server operating systemsLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyespredefined schemeyesyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query language infovia JavaScript builder patternnoyesno
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
HTTP RESTJDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresyesnoyes infoJavayes
TriggersnoUsing read-only observersyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infobased on HBaseShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneselectable replication factor infobased on HBaseMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDBnoyesno
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)noUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standardyes

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More resources
BlazegraphLovefieldSiteWhereSplice MachineWakandaDB
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