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DBMS > AgensGraph vs. Amazon DocumentDB vs. Google Cloud Datastore vs. Ingres vs. Sadas Engine

System Properties Comparison AgensGraph vs. Amazon DocumentDB vs. Google Cloud Datastore vs. Ingres vs. Sadas Engine

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMSSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelGraph DBMS
Relational DBMS
Document storeDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score1.91
Rank#132  Overall
#24  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitebitnine.net/­agensgraphaws.amazon.com/­documentdbcloud.google.com/­datastorewww.actian.com/­databases/­ingreswww.sadasengine.com
Technical documentationbitnine.net/­documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docsdocs.actian.com/­ingreswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperBitnine Global Inc.GoogleActian CorporationSADAS s.r.l.
Initial release2016201920081974 infooriginally developed at University Berkely in early 1970s2006
Current release2.1, December 201811.2, May 20228.0
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialcommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCCC++
Server operating systemsLinux
OS X
Windows
hostedhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
AIX
Linux
Windows
Data schemedepending on used data modelschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, 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.nononono infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)yesyes
APIs and other access methodsCypher Query Language
JDBC
proprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
Java
JavaScript
Python
Go
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresyesnousing Google App Engineyesno
TriggersnonoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancenoneShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication using PaxosIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes
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.nononoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
AgensGraphAmazon DocumentDBGoogle Cloud DatastoreIngresSadas Engine
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