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DBMS > Google Cloud Datastore vs. Microsoft SQL Server vs. QuestDB vs. SAP HANA vs. Sphinx

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

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft SQL Server  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 PlatformMicrosofts flagship relational DBMSA high performance open source SQL database for time series dataIn-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 storeRelational DBMSTime Series DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Relational DBMSDocument store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score44.69
Rank#22  Overall
#16  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­sql-serverquestdb.iowww.sap.com/­products/­hana.htmlsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docslearn.microsoft.com/­en-US/­sql/­sql-serverquestdb.io/­docshelp.sap.com/­hanasphinxsearch.com/­docs
DeveloperGoogleMicrosoftQuestDB Technology IncSAPSphinx Technologies Inc.
Initial release20081989201420102001
Current releaseSQL Server 2022, November 20222.0 SPS07 (April 4, 2023), April 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono 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.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC++Java (Zero-GC), C++, RustC++
Server operating systemshostedLinux
Windows
Linux
macOS
Windows
Appliance or cloud-serviceFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoschema-free via InfluxDB Line Protocolyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyesno
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.noyesnono
Secondary indexesyesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)yesSQL with time-series extensionsyesSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App EngineTransact SQL, .NET languages, R, Python and (with SQL Server 2019) JavanoSQLScript, Rno
TriggersCallbacks using the Google Apps Engineyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationhorizontal 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 Paxosyes, but depending on the SQL-Server EditionSource-replica replication with eventual consistencyyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID for single-table writesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyesyes infothrough memory mapped filesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesno
More information provided by the system vendor
Google Cloud DatastoreMicrosoft SQL ServerQuestDBSAP HANASphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
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