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

DBMS > OrigoDB vs. ReductStore vs. Solr vs. Spark SQL

System Properties Comparison OrigoDB vs. ReductStore vs. Solr vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameOrigoDB  Xexclude from comparisonReductStore  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA fully ACID in-memory object graph databaseDesigned 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.A widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Object oriented DBMS
Time Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteorigodb.comgithub.com/­reductstore
www.reduct.store
solr.apache.orgspark.apache.org/­sql
Technical documentationorigodb.com/­docswww.reduct.store/­docssolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRobert Friberg et alReductStore LLCApache Software FoundationApache Software Foundation
Initial release2009 infounder the name LiveDB202320062014
Current release1.9, March 20249.6.1, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoBusiness Source License 1.1Open Source infoApache Version 2Open Source infoApache 2.0
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#C++, RustJavaScala
Server operating systemsLinux
Windows
Docker
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateUser defined using .NET types and collectionsyes infosupports customizable data types and automatic typingyes
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.no infocan be achieved using .NETyesno
Secondary indexesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLnoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methods.NET Client API
HTTP API
LINQ
HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.NetC++
JavaScript (Node.js)
Python
Rust
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesJava pluginsno
Triggersyes infoDomain Eventsyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoclient side managed; servers are not synchronizedShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritydepending on modelnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlRole based authorizationyesno

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
OrigoDBReductStoreSolrSpark SQL
DB-Engines blog posts

Elasticsearch replaced Solr as the most popular search engine
12 January 2016, Paul Andlinger

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

SOLR-led walkout demands better conditions for Compass workers
27 February 2024, Daily Northwestern

Solr Network Launches Groundbreaking Solana Token Creator
28 May 2024, AccessWire

(SOLR) Proactive Strategies
27 May 2024, news.stocktradersdaily.com

Have Insiders Been Buying Solar Alliance Energy Inc. (CVE:SOLR) Shares?
27 May 2024, Yahoo Movies UK

SOLR hosts teach-in of labor movements at Northwestern
28 January 2024, Daily Northwestern

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

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

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

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

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