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

DBMS > FatDB vs. InfluxDB vs. Spark SQL vs. Teradata Aster

System Properties Comparison FatDB vs. InfluxDB vs. Spark SQL vs. Teradata Aster

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.DBMS for storing time series, events and metricsSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score26.56
Rank#28  Overall
#1  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.influxdata.com/­products/­influxdb-overviewspark.apache.org/­sql
Technical documentationdocs.influxdata.com/­influxdbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudApache Software FoundationTeradata
Initial release2012201320142005
Current release2.7.5, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#GoScala
Server operating systemsWindowsLinux
OS X infothrough Homebrew
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyesyes
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.nonoyes infoin Aster File Store
Secondary indexesyesnonoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP API
JSON over UDP
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsnonoR packages
Triggersyes infovia applicationsnonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoin enterprise version onlyyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infoin enterprise version onlynoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.yes infoDepending on used storage enginenono
User concepts infoAccess controlno infoCan implement custom security layer via applicationssimple rights management via user accountsnofine grained access rights according to SQL-standard
More information provided by the system vendor
FatDBInfluxDBSpark SQLTeradata Aster
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
News

Sync Data from InfluxDB v2 to v3 With the Quix Template
8 April 2024

Infrastructure Monitoring Basics: Getting Started with Telegraf, InfluxDB, and Grafana
5 April 2024

Comparing Dates in Java: A Tutorial
3 April 2024

Python ARIMA Tutorial
29 March 2024

Time Series, InfluxDB, and Vector Databases
26 March 2024

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

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

More resources
FatDBInfluxDBSpark SQLTeradata Aster
DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services
14 March 2024, AWS Blog

Amazon Timestream: Managed InfluxDB for Time Series Data
14 March 2024, The New Stack

InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World
14 March 2024, Business Wire

How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency
15 March 2024, Datanami

AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB
5 April 2024, VentureBeat

provided by Google News

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

Cloudera: Impala's it for interactive SQL on Hadoop; everything else will move to Spark
11 April 2024, Yahoo Movies Canada

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

provided by Google News

Mellanox InfiniBand Helps Accelerate Teradata Aster Big Analytics Appliance
23 April 2024, Yahoo Movies UK

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

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

Neo4j logo

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

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.

SingleStore logo

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

Milvus logo

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

Present your product here