DBMS > Elasticsearch vs. Solr vs. Sqrrl

System Properties Comparison Elasticsearch vs. Solr vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A widely used distributed, scalable search engine based on Apache Lucene

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	151.25
Rank	#8	Overall
	#1	Search engines

Score	52.48
Rank	#20	Overall
	#3	Search engines

Website

www.elastic.co/elasticsearch

lucene.apache.org/solr

sqrrl.com

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

lucene.apache.org/solr/resources.html

Developer

Elastic

Apache Software Foundation

Amazon

originally Sqrrl Data, Inc.

Initial release

2010

2006

2012

Current release

7.8.0, June 2020

8.7.0, November 2020

License

Commercial or Open Source

Open Source

Apache Version 2; Elastic License

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Elasticsearch Service on Elastic Cloud: Try out the official hosted Elasticsearch and Kibana offering available on Amazon Web Services, Google Cloud and Microsoft Azure that's powered by the creators of Elasticsearch.

Implementation language

Java

Server operating systems

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

Solr Parallel SQL Interface

APIs and other access methods

Java API
RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

by using the 'percolation' feature

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

optimistic locking

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Memcached and Redis integration

yes

User concepts

Access control

yes

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

More information provided by the system vendor

Specific characteristics

Elasticsearch is an open source search and analytics engine. As the heart of the...
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Competitive advantages

Open source Real-time indexsearch, and analysis Horizontally scalable Distributed...
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Typical application scenarios

Enterprise search (search experiences for your workplace, apps, and websites), observability...
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Key customers

Thousands of organizations worldwide, including Cisco, eBay, Goldman Sachs, Microsoft,...
» more

Market metrics

Public as of October 2018 Distributed workforce with 1900+ employees around the globe...
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Licensing and pricing models

The Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash) is free and open source...
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