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DBMS > Google Cloud Datastore vs. KeyDB vs. Manticore Search vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. KeyDB vs. Manticore Search vs. Yaacomo

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKeyDB  Xexclude from comparisonManticore Search  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsMulti-storage database for search, including full-text search.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeKey-value storeSearch engineRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Score0.29
Rank#302  Overall
#21  Search engines
Websitecloud.google.com/­datastoregithub.com/­Snapchat/­KeyDB
keydb.dev
manticoresearch.comyaacomo.com
Technical documentationcloud.google.com/­datastore/­docsdocs.keydb.devmanual.manticoresearch.com
DeveloperGoogleEQ Alpha Technology Ltd.Manticore SoftwareQ2WEB GmbH
Initial release2008201920172009
Current release6.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedLinuxFreeBSD
Linux
macOS
Windows
Android
Linux
Windows
Data schemeschema-freeschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyes, details herepartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesInt, 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 indexesyesyes infoby using the Redis Search moduleyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query languageyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol infoRESP - REdis Serialization ProtocoBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresusing Google App EngineLuauser defined functions
TriggersCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
Synchronous replication based on Galera librarySource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsOptimistic locking, atomic execution of commands blocks and scriptsyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes 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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACLnofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreKeyDBManticore SearchYaacomo
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