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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPrometheus  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen-source Time Series DBMS and monitoring systemA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeTime Series DBMSTime Series DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitecloud.google.com/­datastoreprometheus.ioquestdb.iosphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docsprometheus.io/­docsquestdb.io/­docssphinxsearch.com/­docs
DeveloperGoogleQuestDB Technology IncSphinx Technologies Inc.
Initial release2008201520142001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open 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.
Implementation languageGoJava (Zero-GC), C++, RustC++
Server operating systemshostedLinux
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyes, details hereNumeric data onlyyesno
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.nono infoImport of XML data possibleno
Secondary indexesyesnonoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)noSQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP/JSON APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
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 Enginenonono
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal 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 Paxosyes infoby FederationSource-replica replication with eventual consistencynone
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.noneImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID for single-table writesno
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 infothrough memory mapped files
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono
More information provided by the system vendor
Google Cloud DatastorePrometheusQuestDBSphinx
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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