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DBMS > Google Cloud Datastore vs. MySQL vs. QuestDB vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. MySQL vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMySQL  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used open source RDBMSA high performance, low latency Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMS infoKey/Value like access via memcached APITime Series DBMSSearch engine
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.51
Rank#67  Overall
#10  Document stores
Score1241.64
Rank#2  Overall
#2  Relational DBMS
Score0.31
Rank#260  Overall
#20  Time Series DBMS
Score6.35
Rank#59  Overall
#7  Search engines
Websitecloud.google.com/­datastorewww.mysql.comquestdb.iosphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docsdev.mysql.com/­docquestdb.io/­docs/­introductionsphinxsearch.com/­docs
DeveloperGoogleOracle infosince 2010, originally MySQL AB, then SunQuestDB LimitedSphinx Technologies Inc.
Initial release2008199520142001
Current release8.0.22, 20203.2.1, January 2020
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
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.
ScaleGrid for MySQL: Fully managed MySQL hosting on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
Implementation languageC and C++JavaC++
Server operating systemshostedFreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesno
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.noyesno
Secondary indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)yes infowith proprietary extensionsSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary native API
HTTP RESTProprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
JavaC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App Engineyes infoproprietary syntaxnono
TriggersCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabrichorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
nonenone
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.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infonot for MyISAM storage enginenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infonot for MyISAM storage engineACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept infono user groups or rolesno
More information provided by the system vendor
Google Cloud DatastoreMySQLQuestDBSphinx
Specific characteristicsRelational model with native time series support Column based storage and time partitioned...
» more
Competitive advantagesReal-time data ingestion and istant SQL queries for time series High performance...
» more
Typical application scenariosApplication metrics Financial market data and algo trading DevOps monitoring Real-time...
» more
Licensing and pricing modelsApache 2.0.
» more

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Google Cloud DatastoreMySQLQuestDBSphinx
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