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

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

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, low latency Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document storeTime Series DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.99
Rank#169  Overall
#27  Document stores
#30  Key-value stores
#83  Relational DBMS
Score5.51
Rank#67  Overall
#10  Document stores
Score0.31
Rank#260  Overall
#20  Time Series DBMS
Score6.35
Rank#59  Overall
#7  Search engines
Websitewww.foundationdb.orgcloud.google.com/­datastorequestdb.iosphinxsearch.com
Technical documentationapple.github.io/­foundationdbcloud.google.com/­datastore/­docsquestdb.io/­docs/­introductionsphinxsearch.com/­docs
DeveloperFoundationDBGoogleQuestDB LimitedSphinx Technologies Inc.
Initial release2013200820142001
Current release6.2.11, November 20193.2.1, January 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++
Server operating systemsLinux
OS X
Windows
hostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-free infosome layers support schemasschema-freeyesyes
Typing infopredefined data types such as float or dateno infosome layers support typingyes, details hereyesno
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
Secondary indexesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query language (GQL)SQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTProprietary protocol
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresin SQL-layer onlyusing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenono
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 nodesyesMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable 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.Immediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlyyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID 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.nono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
FoundationDBGoogle Cloud DatastoreQuestDBSphinx
Specific characteristicsRelational model with native time series support Column based storage and time partitioned...
» more
Competitive advantagesReal-time data ingestion and istant SQL queries for time series High performance...
» more
Typical application scenariosApplication metrics Financial market data and algo trading DevOps monitoring Real-time...
» more
Licensing and pricing modelsApache 2.0.
» more

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More resources
FoundationDBGoogle Cloud DatastoreQuestDBSphinx
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