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DBMS > FatDB vs. Heroic vs. SingleStore vs. Solr

System Properties Comparison FatDB vs. Heroic vs. SingleStore vs. Solr

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonHeroic  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSolr  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score5.60
Rank#62  Overall
#35  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitegithub.com/­spotify/­heroicwww.singlestore.comsolr.apache.org
Technical documentationspotify.github.io/­heroicdocs.singlestore.comsolr.apache.org/­resources.html
DeveloperFatCloudSpotifySingleStore Inc.Apache Software Foundation
Initial release2012201420132006
Current release8.5, January 20249.5.0, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree developer edition availableOpen Source infoApache Version 2
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.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC#JavaC++, GoJava
Server operating systemsWindowsLinux info64 bit version requiredAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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
Secondary indexesyesyes infovia Elasticsearchyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLno infoVia inetgration in SQL Servernoyes infobut no triggers and foreign keysSolr Parallel SQL Interface
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC#Bash
C
C#
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infovia applicationsnoyesJava plugins
Triggersyes infovia applicationsnonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infohash partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replication infostores two copies of each physical data partition on two separate nodesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono infocan define user-defined aggregate functions for map-reduce-style calculationsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsFine grained access control via users, groups and rolesyes
More information provided by the system vendor
FatDBHeroicSingleStore infoformer name was MemSQLSolr
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
FatDBHeroicSingleStore infoformer name was MemSQLSolr
DB-Engines blog posts

Turbocharge Your Application Development Using WebAssembly With SingleStoreDB
17 October 2022,  Akmal Chaudhri, SingleStore (sponsor) 

Cloud-Based Analytics With SingleStoreDB
9 June 2022,  Akmal Chaudhri, SingleStore (sponsor) 

SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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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

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