DBMS > AlaSQL vs. LokiJS vs. SingleStore vs. Solr vs. SQLite

System Properties Comparison AlaSQL vs. LokiJS vs. SingleStore vs. Solr vs. SQLite

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

In-memory JavaScript DBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

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

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

alasql.org

github.com/techfort/LokiJS

www.singlestore.com

solr.apache.org

www.sqlite.org

Technical documentation

github.com/AlaSQL/alasql

techfort.github.io/LokiJS

docs.singlestore.com

solr.apache.org/resources.html

www.sqlite.org/docs.html

Developer

Andrey Gershun & Mathias R. Wulff

SingleStore Inc.

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2014

2013

2006

2000

Current release

8.5, January 2024

9.6.0, April 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

commercial

free developer edition available

Open Source

Apache Version 2

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++, Go

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux

64 bit version required

All OS with a Java VM

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

server-less

Data scheme

schema-free

yes

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

but no triggers and foreign keys

Solr Parallel SQL Interface

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

JavaScript

Bash
C
C#
Java
JavaScript (Node.js)
Python

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

hash partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

stores two copies of each physical data partition on two separate nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

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

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

atomic operations within a single collection possible

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Fine grained access control via users, groups and roles

yes

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Licensing and pricing models

F ree Tier and Enterprise Edition
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