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DBMS > FoundationDB vs. QuestDB vs. Sphinx vs. Vertica

System Properties Comparison FoundationDB vs. QuestDB vs. Sphinx vs. Vertica

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparisonVertica infoOpenText™ Vertica™  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.A high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databasesCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Time Series DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitegithub.com/­apple/­foundationdbquestdb.iosphinxsearch.comwww.vertica.com
Technical documentationapple.github.io/­foundationdbquestdb.io/­docssphinxsearch.com/­docsvertica.com/­documentation
DeveloperFoundationDBQuestDB Technology IncSphinx Technologies Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201420012005
Current release6.2.28, November 20203.5.1, February 202312.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustC++C++
Server operating systemsLinux
OS X
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-free infosome layers support schemasyes infoschema-free via InfluxDB Line ProtocolyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateno infosome layers support typingyesnoyes
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 indexesnonoyes infofull-text index on all search fieldsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLsupported in specific SQL layer onlySQL with time-series extensionsSQL-like query language (SphinxQL)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
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
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresin SQL-layer onlynonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with eventual consistencynoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID for single-table writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infothrough memory mapped filesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FoundationDBQuestDBSphinxVertica infoOpenText™ Vertica™
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
Cost-based models and subscription-based models are both available. One license is...
» more
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More resources
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