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DBMS > Google Cloud Datastore vs. InfluxDB vs. JanusGraph vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. InfluxDB vs. JanusGraph vs. Sphinx

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeTime Series DBMSGraph DBMSSearch engine
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
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewjanusgraph.orgsphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbdocs.janusgraph.orgsphinxsearch.com/­docs
DeveloperGoogleLinux Foundation; originally developed as Titan by AureliusSphinx Technologies Inc.
Initial release2008201320172001
Current release2.7.6, April 20240.6.3, February 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoMIT-License; commercial enterprise version 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.
Implementation languageGoJavaC++
Server operating systemshostedLinux
OS X infothrough Homebrew
Linux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereNumeric data and Stringsyesno
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 languagenoSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Proprietary protocol
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
Clojure
Java
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App Enginenoyesno
TriggersCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoin enterprise version onlyyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)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 Paxosselectable replication factor infoin enterprise version onlyyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes infovia Faunus, a graph analytics engineno
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.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphsno
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 datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes 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.noyes infoDepending on used storage engine
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsUser authentification and security via Rexster Graph Serverno
More information provided by the system vendor
Google Cloud DatastoreInfluxDBJanusGraph infosuccessor of TitanSphinx
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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