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DBMS > Amazon DocumentDB vs. Cubrid vs. Google Cloud Datastore vs. Sphinx vs. Transwarp Hippo

System Properties Comparison Amazon DocumentDB vs. Cubrid vs. Google Cloud Datastore vs. Sphinx vs. Transwarp Hippo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCubrid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSphinx  Xexclude from comparisonTranswarp Hippo  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen source search engine for searching in data from different sources, e.g. relational databasesCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelDocument storeRelational DBMSDocument storeSearch engineVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.05
Rank#386  Overall
#15  Vector DBMS
Websiteaws.amazon.com/­documentdbcubrid.com (korean)
cubrid.org (english)
cloud.google.com/­datastoresphinxsearch.comwww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationaws.amazon.com/­documentdb/­resourcescubrid.org/­manualscloud.google.com/­datastore/­docssphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationGoogleSphinx Technologies Inc.
Initial release20192008200820012023
Current release11.0, January 20213.5.1, February 20231.0, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availablecommercial
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 languageC, C++, JavaC++C++
Server operating systemshostedLinux
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details herenoVector, Numeric and String
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
Secondary indexesyesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLnoyesSQL-like query language (GQL)SQL-like query language (SphinxQL)no
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
OLE DB
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocolRESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresusing Google App Enginenono
TriggersnoyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replicationMulti-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes 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 Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noRole based access control and fine grained access rights

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More resources
Amazon DocumentDBCubridGoogle Cloud DatastoreSphinxTranswarp Hippo
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