DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Ignite vs. Solr vs. Spark SQL vs. Trafodion

System Properties Comparison Ignite vs. Solr vs. Spark SQL vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value store
Relational DBMS
Search engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteignite.apache.orgsolr.apache.orgspark.apache.org/­sqltrafodion.apache.org
Technical documentationapacheignite.readme.io/­docssolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperApache Software FoundationApache Software FoundationApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2015200620142014
Current releaseApache Ignite 2.69.6.0, April 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open 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++, Java, .NetJavaScalaC++, Java
Server operating systemsLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic 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.yesyesnono
Secondary indexesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL InterfaceSQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Java pluginsnoJava Stored Procedures
Triggersyes (cache interceptors and events)yes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnoACID
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.yesyesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsyesnofine grained access rights according to SQL-standard

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
IgniteSolrSpark SQLTrafodion
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

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

Apache Ignite: An Overview
6 September 2023, Open Source For You

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

Fire up big data processing with Apache Ignite
27 October 2016, InfoWorld

provided by Google News

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

Closing Bell: Solar Alliance Energy Inc flat on Tuesday (SOLR)
24 May 2024, The Globe and Mail

(SOLR) Technical Data
17 May 2024, news.stocktradersdaily.com

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

SOLR hosts May Day amid ongoing contract negotiations
12 May 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

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

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



Share this page

Featured Products

Neo4j logo

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

Milvus logo

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

SingleStore logo

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

RaimaDB logo

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

Present your product here