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DBMS > EsgynDB vs. FeatureBase vs. Solr vs. TimescaleDB vs. Typesense

System Properties Comparison EsgynDB vs. FeatureBase vs. Solr vs. TimescaleDB vs. Typesense

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFeatureBase  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.A widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMSRelational DBMSSearch engineTime Series DBMSSearch engine
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score0.26
Rank#304  Overall
#138  Relational DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Score0.91
Rank#203  Overall
#14  Search engines
Websitewww.esgyn.cnwww.featurebase.comsolr.apache.orgwww.timescale.comtypesense.org
Technical documentationdocs.featurebase.comsolr.apache.org/­resources.htmldocs.timescale.comtypesense.org/­docs
DeveloperEsgynMolecula and Pilosa Open Source ContributorsApache Software FoundationTimescale
Initial release20152017200620172015
Current release2022, May 20229.5.0, February 20242.13.0, November 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPL V3
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++, JavaGoJavaCC++
Server operating systemsLinuxLinux
macOS
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 schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nonoyesyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLyesSQL queriesSolr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
JDBC
Kafka Connector
ODBC
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresJava Stored ProceduresJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersnonoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesyesSource-replica replication with hot standby and reads on replicas infoMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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More resources
EsgynDBFeatureBaseSolrTimescaleDBTypesense
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