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

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

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically 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 modelDocument storeRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orgcloud.google.com/­datastorewww.actian.com/­databases/­ingreswww.sadasengine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.actian.com/­ingreswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperApache Software FoundationGoogleActian CorporationSADAS s.r.l.
Initial release2019201420081974 infooriginally developed at University Berkely in early 1970s2006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.2, May 20228.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemshostedLinux
Unix
Windows
hostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
AIX
Linux
Windows
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesschema-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 SQLnoyesSQL-like query language (GQL)yesyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineyesno
TriggersnonoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication
Source-replica replication
Multi-source replication using PaxosIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual 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 integrityno infotypically not used, however similar functionality with DBRef possiblenoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID 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.yesnonoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess 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
Amazon DocumentDBApache PhoenixGoogle Cloud DatastoreIngresSadas Engine
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