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DBMS > atoti vs. Blazegraph vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Yaacomo

System Properties Comparison atoti vs. Blazegraph vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Yaacomo

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonBlazegraph  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonYaacomo  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelObject oriented DBMSGraph DBMS
RDF store
Document storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score14.29
Rank#39  Overall
#6  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Websiteatoti.ioblazegraph.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­datastoreyaacomo.com
Technical documentationdocs.atoti.iowiki.blazegraph.comfirebase.google.com/­docs/­databasecloud.google.com/­datastore/­docs
DeveloperActiveViamBlazegraphGoogle infoacquired by Google 2014GoogleQ2WEB GmbH
Initial release2006201220082009
Current release2.1.5, March 2019
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoextended commercial license availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
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
hostedhostedAndroid
Linux
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infoRDF literal typesyesyes, details hereyes
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 indexesyesyesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)SPARQL is used as query languagenoSQL-like query language (GQL)yes
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresPythonyeslimited functionality with using 'rules'using Google App Engine
TriggersnoCallbacks are triggered when data changesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
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.Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.yesnoyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)yes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
atotiBlazegraphFirebase Realtime DatabaseGoogle Cloud DatastoreYaacomo
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