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DBMS > FatDB vs. Galaxybase vs. Google Cloud Datastore vs. InfluxDB vs. Spark SQL

System Properties Comparison FatDB vs. Galaxybase vs. Google Cloud Datastore vs. InfluxDB vs. Spark SQL

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGalaxybase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable, ACID-compliant native distributed parallel graph platformAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Graph DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#39  Graph DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegalaxybase.comcloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewspark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudChuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司GoogleApache Software Foundation
Initial release20122017200820132014
Current releaseNov 20, November 20212.7.6, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C and JavaGoScala
Server operating systemsWindowsLinuxhostedLinux
OS X infothrough Homebrew
Linux
OS X
Windows
Data schemeschema-freeStrong typed schemaschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereNumeric data and Stringsyes
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.nononono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like query language (GQL)SQL-like query languageSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
JDBC
ODBC
Supported programming languagesC#Go
Java
Python
.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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsuser defined procedures and functionsusing Google App Enginenono
Triggersyes infovia applicationsCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoin enterprise version onlyyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosselectable replication factor infoin enterprise version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate 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.
Foreign keys infoReferential integritynoyes infoRelationships in graphsyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoDepending on used storage engineno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsno
More information provided by the system vendor
FatDBGalaxybaseGoogle Cloud DatastoreInfluxDBSpark SQL
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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