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DBMS > AgensGraph vs. Drizzle vs. Google Cloud Datastore vs. RavenDB vs. SQream DB

System Properties Comparison AgensGraph vs. Drizzle vs. Google Cloud Datastore vs. RavenDB vs. SQream DB

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRavenDB  Xexclude from comparisonSQream DB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen Source Operational and Transactional Enterprise NoSQL Document Databasea GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSDocument storeDocument storeRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#320  Overall
#29  Graph DBMS
#143  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score2.68
Rank#102  Overall
#19  Document stores
Score0.62
Rank#234  Overall
#109  Relational DBMS
Websitebitnine.net/­agensgraphcloud.google.com/­datastoreravendb.netsqream.com
Technical documentationbitnine.net/­documentationcloud.google.com/­datastore/­docsravendb.net/­docsdocs.sqream.com
DeveloperBitnine Global Inc.Drizzle project, originally started by Brian AkerGoogleHibernating RhinosSQream Technologies
Initial release20162008200820102017
Current release2.1, December 20187.2.4, September 20125.4, July 20222022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoGNU GPLcommercialOpen Source infoAGPL version 3, commercial license availablecommercial
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 languageCC++C#C++, CUDA, Haskell, Java, Scala
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
OS X
hostedLinux
macOS
Raspberry Pi
Windows
Linux
Data schemedepending on used data modelyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details herenoyes, ANSI Standard SQL Types
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.nono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like query language (GQL)SQL-like query language (RQL)yes
APIs and other access methodsCypher Query Language
JDBC
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
.Net
JDBC
ODBC
Supported programming languagesC
Java
JavaScript
Python
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnousing Google App Engineyesuser defined functions in Python
Triggersnono infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardingShardinghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Authorization levels configured per client per database

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More resources
AgensGraphDrizzleGoogle Cloud DatastoreRavenDBSQream DB
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