DBMS > Solr vs. SQream DB vs. Sqrrl

System Properties Comparison Solr vs. SQream DB 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 widely used distributed, scalable search engine based on Apache Lucene

a GPU-based, columnar RDBMS for big data analytics workloads

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Search engine

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	56.61
Rank	#20	Overall
	#3	Search engines

Score	0.58
Rank	#224	Overall
	#108	Relational DBMS

Website

lucene.apache.org/solr

sqream.com

sqrrl.com

Technical documentation

lucene.apache.org/solr/resources.html

docs.sqream.com

Developer

Apache Software Foundation

SQream Technologies

Amazon

originally Sqrrl Data, Inc.

Initial release

2006

2014

2012

Current release

9.0.0, May 2022

2021.2, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, CUDA, Haskell, Java, Scala

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

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

Solr Parallel SQL Interface

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

.Net
JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

Actionscript
C

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

Server-side scripts

Stored procedures

Java plugins

user defined functions in Python

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal and vertical partitioning

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

ACID

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.

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

Due to exponentially growing data, organizations today are facing slowdowns, with...
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Competitive advantages

Much faster time to insight Analyze significantly more data Achieve previously unobtainable...
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Typical application scenarios

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Key customers

Some of our customers include: LG Uplus, AIS (Advanced Info Service), ACL Mobile,...
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News

Women in Tech: “Positions and opportunities in the technology field are endless”
7 June 2022

Minimizing the carbon footprint of data analysis, maximizing sustainability for data centers
7 June 2022

SQream at Asia Tech x Singapore 2022: Big Data and AI Crucial for Customer Experience and QoS
2 June 2022

SQream Appoints Naama Saar as New COO
16 May 2022

Panoply Partners with Square to Offer Simplified Business Intelligence
16 May 2022

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More resources

DB-Engines blog posts

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12 January 2016, Paul Andlinger

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2 July 2014, Paul Andlinger

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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