DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Redshift vs. FoundationDB vs. Spark SQL vs. Stardog

System Properties Comparison Amazon Redshift vs. FoundationDB vs. Spark SQL vs. Stardog

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonFoundationDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionLarge scale data warehouse service for use with business intelligence toolsOrdered key-value store. Core features are complimented by layers.Spark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.63
Rank#33  Overall
#20  Relational DBMS
Score1.50
Rank#166  Overall
#29  Document stores
#27  Key-value stores
#76  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score2.03
Rank#136  Overall
#12  Graph DBMS
#6  RDF stores
Websiteaws.amazon.com/­redshiftgithub.com/­apple/­foundationdbspark.apache.org/­sqlwww.stardog.com
Technical documentationdocs.aws.amazon.com/­redshiftapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperAmazon (based on PostgreSQL)FoundationDBApache Software FoundationStardog-Union
Initial release2012201320142010
Current release6.2.28, November 20203.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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 languageCC++ScalaJava
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesschema-free infosome layers support schemasyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesno infosome layers support typingyesyes
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 infoImport/export of XML data possible
Secondary indexesrestrictednonoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardsupported in specific SQL layer onlySQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Pythonin SQL-layer onlynouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnononoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemin SQL-layer onlynoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoAccess rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon RedshiftFoundationDBSpark SQLStardog
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

show all

Recent citations in the news

Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics ...
27 March 2024, AWS Blog

Unlock insights on Amazon RDS for MySQL data with zero-ETL integration to Amazon Redshift | Amazon Web Services
21 March 2024, AWS Blog

Amazon Redshift adds new AI capabilities, including Amazon Q, to boost efficiency and productivity | Amazon Web ...
29 November 2023, AWS Blog

Data Tokenization with Amazon Redshift Dynamic Data Masking and Protegrity | Amazon Web Services
4 March 2024, AWS Blog

The Composable CDP: Activating Data from Amazon Redshift to 200+ Tools Using Hightouch | Amazon Web Services
4 March 2024, AWS Blog

provided by Google News

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
25 March 2024, Simplilearn

Run Spark SQL on Amazon Athena Spark | AWS Big Data Blog
23 October 2023, AWS Blog

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Present your product here