DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Redshift vs. Bangdb vs. FoundationDB vs. Spark SQL vs. TempoIQ

System Properties Comparison Amazon Redshift vs. Bangdb vs. FoundationDB vs. Spark SQL vs. TempoIQ

Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonBangdb  Xexclude from comparisonFoundationDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTempoIQ infoformerly TempoDB  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.
DescriptionLarge scale data warehouse service for use with business intelligence toolsConverged and high performance database for device data, events, time series, document and graphOrdered key-value store. Core features are complimented by layers.Spark SQL is a component on top of 'Spark Core' for structured data processingScalable analytics DBMS for sensor data, provided as a service (SaaS)
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­redshiftbangdb.comgithub.com/­apple/­foundationdbspark.apache.org/­sqltempoiq.com (offline)
Technical documentationdocs.aws.amazon.com/­redshiftdocs.bangdb.comapple.github.io/­foundationdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)Sachin Sinha, BangDBFoundationDBApache Software FoundationTempoIQ
Initial release20122012201320142012
Current releaseBangDB 2.0, October 20216.2.28, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD 3Open Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, C++C++Scala
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-free infosome layers support schemasyesschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsno 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 indexesrestrictedyes infosecondary, composite, nested, reverse, geospatialnono
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL like support with command line toolsupported in specific SQL layer onlySQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Python
R
Scala
C#
Java
JavaScript infoNode.js
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Pythonnoin SQL-layer onlynono
Triggersnoyes, Notifications (with Streaming only)nonoyes infoRealtime Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor, Knob for CAP (enterprise version only)yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable consistency, set CAP knob accordinglyLinearizable consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoin SQL-layer onlynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modenono
User concepts infoAccess controlfine grained access rights according to SQL-standardyes (enterprise version only)nonosimple authentication-based access control

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 RedshiftBangdbFoundationDBSpark SQLTempoIQ infoformerly TempoDB
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

Amazon Redshift Serverless is now generally available in the AWS China (Ningxia) Region - AWS
28 May 2024, AWS Blog

AWS analytics services streamline user access to data, permissions setting, and auditing | Amazon Web Services
29 May 2024, AWS Blog

Simplify data lake access control for your enterprise users with trusted identity propagation in AWS IAM Identity Center ...
29 May 2024, AWS Blog

Build a decentralized semantic search engine on heterogeneous data stores using autonomous agents | Amazon Web ...
28 May 2024, AWS Blog

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

provided by Google News

FoundationDB Raises $17 Million Series A Financing
26 May 2024, Yahoo Movies UK

FoundationDB team's new venture, Antithesis, raises $47M to enhance software testing
13 February 2024, SiliconANGLE News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

Antithesis raises $47M to launch an automated testing platform for software
13 February 2024, TechCrunch

Deno adds scaleable messaging with new Queues feature, sparks debate about proprietary services • DEVCLASS
28 September 2023, DevClass

provided by Google News

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

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

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

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

Milvus logo

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

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

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

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

Present your product here