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DBMS > Google Cloud Datastore vs. InfluxDB vs. Oracle Berkeley DB vs. Prometheus

System Properties Comparison Google Cloud Datastore vs. InfluxDB vs. Oracle Berkeley DB vs. Prometheus

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsWidely used in-process key-value storeOpen-source Time Series DBMS and monitoring system
Primary database modelDocument storeTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Websitecloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlprometheus.io
Technical documentationcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlprometheus.io/­docs
DeveloperGoogleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2008201319942015
Current release2.7.6, April 202418.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infocommercial license availableOpen Source infoApache 2.0
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 languageGoC, Java, C++ (depending on the Berkeley DB edition)Go
Server operating systemshostedLinux
OS X infothrough Homebrew
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereNumeric data and StringsnoNumeric data only
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.nonoyes infoonly with the Berkeley DB XML editionno infoImport of XML data possible
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Enginenonono
TriggersCallbacks using the Google Apps Enginenoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoin enterprise version onlynoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infoin enterprise version onlySource-replica replicationyes infoby Federation
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.none
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 TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoDepending on used storage engineyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsnono
More information provided by the system vendor
Google Cloud DatastoreInfluxDBOracle Berkeley DBPrometheus
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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