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DBMS > Amazon DocumentDB vs. Google Cloud Datastore vs. Sphinx vs. TDSQL for MySQL vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Google Cloud Datastore vs. Sphinx vs. TDSQL for MySQL vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSphinx  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAutomatically 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 databasesA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeDocument storeSearch engineRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score4.49
Rank#79  Overall
#12  Document stores
Score6.03
Rank#60  Overall
#6  Search engines
Score0.82
Rank#213  Overall
#97  Relational DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastoresphinxsearch.comwww.tencentcloud.com/­products/­dcdbyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docssphinxsearch.com/­docswww.tencentcloud.com/­document/­product/­1042
DeveloperGoogleSphinx Technologies Inc.TencentQ2WEB GmbH
Initial release20192008200120132009
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
hostedAndroid
Linux
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details herenoyesyes
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 indexesyesyesyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query language (SphinxQL)yesyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocolJDBC
ODBC
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.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
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Enginenoyes
TriggersnoCallbacks using the Google Apps Enginenoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedAutomatic shardinghorizontal 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 using PaxosnoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infousing Google Cloud Dataflownonono
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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
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 rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBGoogle Cloud DatastoreSphinxTDSQL for MySQLYaacomo
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