DB-EnginesextremeDB - solve IoT connectivity disruptionsEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Apache Spark (SQL) vs. Microsoft Azure Table Storage vs. ReductStore

System Properties Comparison Apache Spark (SQL) vs. Microsoft Azure Table Storage vs. ReductStore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonReductStore  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingA Wide Column Store for rapid development using massive semi-structured datasetsDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSWide column storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.40
Rank#29  Overall
#18  Relational DBMS
Score2.63
Rank#94  Overall
#7  Wide column stores
Score0.05
Rank#357  Overall
#37  Time Series DBMS
Websitespark.apache.org/­sqlazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­reductstore
www.reduct.store
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.reduct.store/­docs
DeveloperApache Software FoundationMicrosoftReductStore LLC
Initial release201420122023
Current release3.5.0 ( 2.13), September 20231.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++, Rust
Server operating systemsLinux
OS X
Windows
hostedDocker
Linux
macOS
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesyes
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 indexesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIHTTP API
Supported programming languagesJava
Python
R
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signatures

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

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

More resources
Apache Spark (SQL)Microsoft Azure Table StorageReductStore
Recent citations in the news

Introducing AWS Glue 5.0 for Apache Spark
4 December 2024, Amazon Web Services

How to run Pandas code on Spark
25 January 2025, Theodo Data & AI

18 top big data tools and technologies to know about in 2025
22 January 2025, TechTarget

Kyuubi + Spark: Power of Big Data | by Aleksei Aleinikov | Feb, 2025
20 February 2025, DataDrivenInvestor

30 Azure Databricks Interview Questions and Answers (2025)
14 April 2025, Simplilearn.com

provided by Google News

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

AWS vs Azure vs Google Cloud in 2025: Cloud Comparison
6 April 2025, Cloudwards.net

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn.com

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, HackerNoon

Inside Azure File Storage
7 October 2015, Microsoft Azure

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

SingleStore logo

The data platform to build your intelligent applications.
Try it 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.

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