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DBMS > Google Cloud Datastore vs. QuestDB vs. SAP HANA vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. QuestDB vs. SAP HANA vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonQuestDB  Xexclude from comparisonSAP HANA  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, low latency Time Series DBMSIn-memory, column based data store. Available as appliance or cloud serviceOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeTime Series DBMSRelational DBMSSearch engine
Secondary database modelsRelational DBMSDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.51
Rank#67  Overall
#10  Document stores
Score0.31
Rank#260  Overall
#20  Time Series DBMS
Score53.58
Rank#19  Overall
#13  Relational DBMS
Score6.35
Rank#59  Overall
#7  Search engines
Websitecloud.google.com/­datastorequestdb.iowww.sap.com/­products/­hana.htmlsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docsquestdb.io/­docs/­introductionhelp.sap.com/­hanasphinxsearch.com/­docs
DeveloperGoogleQuestDB LimitedSAPSphinx Technologies Inc.
Initial release2008201420102001
Current release2.0 SPS04 (April 5, 2019), April 20193.2.1, January 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnono infoalso available as a cloud based serviceno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedLinux
macOS
Windows
Appliance or cloud-serviceFreeBSD
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.nonono
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageyesSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App EnginenoSQLScript, Rno
TriggersCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)yesSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneyesnone
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 pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID for single-table writesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesno
More information provided by the system vendor
Google Cloud DatastoreQuestDBSAP HANASphinx
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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More resources
Google Cloud DatastoreQuestDBSAP HANASphinx
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