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DBMS > Apache Druid vs. EsgynDB vs. Solr vs. SurrealDB

System Properties Comparison Apache Druid vs. EsgynDB vs. Solr vs. SurrealDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEsgynDB  Xexclude from comparisonSolr  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA widely used distributed, scalable search engine based on Apache LuceneA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSSearch engineDocument store
Graph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websitedruid.apache.orgwww.esgyn.cnsolr.apache.orgsurrealdb.com
Technical documentationdruid.apache.org/­docs/­latest/­designsolr.apache.org/­resources.htmlsurrealdb.com/­docs
DeveloperApache Software Foundation and contributorsEsgynApache Software FoundationSurrealDB Ltd
Initial release2012201520062022
Current release29.0.1, April 20249.5.0, February 2024v1.1.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2Open Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaJavaRust
Server operating systemsLinux
OS X
Unix
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyesyes 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.nonoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL for queryingyesSolr Parallel SQL InterfaceSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresnoJava Stored ProceduresJava plugins
Triggersnonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication between multi datacentersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardyesyes, based on authentication and database rules

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More resources
Apache DruidEsgynDBSolrSurrealDB
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