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DBMS > Ignite vs. Solr vs. TDengine

System Properties Comparison Ignite vs. Solr vs. TDengine

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Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonSolr  Xexclude from comparisonTDengine  Xexclude from comparison
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 LuceneTime Series DBMS and big data platform
Primary database modelKey-value store
Relational DBMS
Search engineTime Series DBMS
Secondary database modelsSpatial DBMSRelational 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
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websiteignite.apache.orgsolr.apache.orggithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationapacheignite.readme.io/­docssolr.apache.org/­resources.htmldocs.tdengine.com
DeveloperApache Software FoundationApache Software FoundationTDEngine, previously Taos Data
Initial release201520062019
Current releaseApache Ignite 2.69.6.0, April 20243.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetJavaC
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
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes 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.yesyesno
Secondary indexesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL InterfaceStandard SQL with extensions for time-series applications
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
JDBC
RESTful HTTP API
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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Java pluginsno
Triggersyes (cache interceptors and events)yes infoUser configurable commands triggered on index changesyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesyes
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 reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsyesyes
More information provided by the system vendor
IgniteSolrTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
IgniteSolrTDengine
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Recent citations in the news

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27 February 2024, Daily Northwestern

Best Practices from Rackspace for Modernizing a Legacy HBase/Solr Architecture Using AWS Services | Amazon Web ...
9 October 2023, AWS Blog

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

SearchStax Launches Serverless Solr Service to Accelerate Cloud-Native Application Development
5 April 2023, PR Newswire

How to import data into Apache Solr
17 May 2022, TechRepublic

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TDengine debuts cloud-based time-series data processing platform for IoT deployments
20 September 2022, SiliconANGLE News

New TDengine Benchmark Results Show Up to 37.0x Higher Query Performance Than InfluxDB and TimescaleDB
28 February 2023, GlobeNewswire

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

provided by Google News



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