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DBMS > EsgynDB vs. QuestDB vs. Realm vs. Solr vs. Yaacomo

System Properties Comparison EsgynDB vs. QuestDB vs. Realm vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonQuestDB  Xexclude from comparisonRealm  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA high performance open source SQL database for time series dataA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSTime Series DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cnquestdb.iorealm.iosolr.apache.orgyaacomo.com
Technical documentationquestdb.io/­docsrealm.io/­docssolr.apache.org/­resources.html
DeveloperEsgynQuestDB Technology IncRealm, acquired by MongoDB in May 2019Apache Software FoundationQ2WEB GmbH
Initial release20152014201420062009
Current release9.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava (Zero-GC), C++, RustJava
Server operating systemsLinuxLinux
macOS
Windows
Android
Backend: server-less
iOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononoyesno
Secondary indexesyesnoyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL with time-series extensionsnoSolr Parallel SQL Interfaceyes
APIs and other access methodsADO.NET
JDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
Java infowith Android only
Objective-C
React Native
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnono inforuns within the applications so server-side scripts are unnecessaryJava plugins
Triggersnonoyes infoChange Listenersyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)noneShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replication with eventual consistencynoneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID for single-table writesACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped filesyes infoIn-Memory realmyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesyesfine grained access rights according to SQL-standard
More information provided by the system vendor
EsgynDBQuestDBRealmSolrYaacomo
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
EsgynDBQuestDBRealmSolrYaacomo
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