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DBMS > Amazon Redshift vs. Databend vs. FoundationDB vs. Spark SQL vs. WakandaDB

System Properties Comparison Amazon Redshift vs. Databend vs. FoundationDB vs. Spark SQL vs. WakandaDB

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonDatabend  Xexclude from comparisonFoundationDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonWakandaDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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 toolsAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityOrdered key-value store. Core features are complimented by layers.Spark SQL is a component on top of 'Spark Core' for structured data processingWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­redshiftgithub.com/­datafuselabs/­databend
www.databend.com
github.com/­apple/­foundationdbspark.apache.org/­sqlwakanda.github.io
Technical documentationdocs.aws.amazon.com/­redshiftdocs.databend.comapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperAmazon (based on PostgreSQL)Databend LabsFoundationDBApache Software FoundationWakanda SAS
Initial release20122021201320142012
Current release1.0.59, April 20236.2.28, November 20203.5.0 ( 2.13), September 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCRustC++ScalaC++, JavaScript
Server operating systemshostedhosted
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesschema-free infosome layers support schemasyesyes
Typing infopredefined data types such as float or dateyesyesno 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.nononono
Secondary indexesrestrictednonono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardyessupported in specific SQL layer onlySQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
CLI Client
JDBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functions infoin Pythonnoin SQL-layer onlynoyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDnoACID
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept, user rolesnonoyes

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More resources
Amazon RedshiftDatabendFoundationDBSpark SQLWakandaDB
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