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DBMS > Amazon DocumentDB vs. Google Cloud Datastore vs. Manticore Search vs. TDSQL for MySQL

System Properties Comparison Amazon DocumentDB vs. Google Cloud Datastore vs. Manticore Search vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.A 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.
Primary database modelDocument storeDocument storeSearch engineRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.22
Rank#312  Overall
#21  Search engines
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastoremanticoresearch.comwww.tencentcloud.com/­products/­dcdb
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docsmanual.manticoresearch.comwww.tencentcloud.com/­document/­product/­1042
DeveloperGoogleManticore SoftwareTencent
Initial release2019200820172013
Current release6.0, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedhostedFreeBSD
Linux
macOS
Windows
hosted
Data schemeschema-freeschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyesyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsyes
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedAutomatic sharding
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 PaxosSynchronous replication based on Galera libraryMulti-source 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 Dataflownono
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 Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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 concept

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More resources
Amazon DocumentDBGoogle Cloud DatastoreManticore SearchTDSQL for MySQL
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