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DBMS > Badger vs. Blazegraph vs. Google Cloud Datastore vs. Memcached vs. Warp 10

System Properties Comparison Badger vs. Blazegraph vs. Google Cloud Datastore vs. Memcached vs. Warp 10

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMemcached  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.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.High-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 PlatformIn-memory key-value store, originally intended for cachingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelKey-value storeGraph DBMS
RDF store
Document storeKey-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score4.36
Rank#72  Overall
#12  Document stores
Score18.08
Rank#32  Overall
#4  Key-value stores
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgerblazegraph.comcloud.google.com/­datastorewww.memcached.orgwww.warp10.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwiki.blazegraph.comcloud.google.com/­datastore/­docsgithub.com/­memcached/­memcached/­wikiwww.warp10.io/­content/­02_Getting_started
DeveloperDGraph LabsBlazegraphGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSenX
Initial release20172006200820032015
Current release2.1.5, March 20191.6.27, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoextended commercial license availablecommercialOpen Source infoBSD licenseOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaCJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
hostedFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenoyes 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 indexesnoyesyesnono
SQL infoSupport of SQLnoSPARQL is used as query languageSQL-like query language (GQL)nono
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocolHTTP API
Jupyter
WebSocket
Supported programming languagesGo.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyesusing Google App Enginenoyes infoWarpScript
TriggersnonoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication using Paxosnone infoRepcached, a Memcached patch, provides this functionallityselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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 Consistency infobased on HBase
Foreign keys infoReferential integritynoyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing SASL (Simple Authentication and Security Layer) protocolMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
BadgerBlazegraphGoogle Cloud DatastoreMemcachedWarp 10
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