DBMS > AlaSQL vs. Manticore Search vs. Postgres-XL vs. Snowflake vs. SQLite

System Properties Comparison AlaSQL vs. Manticore Search vs. Postgres-XL vs. Snowflake vs. SQLite

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Multi-storage database for search, including full-text search.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Cloud-based data warehousing service for structured and semi-structured data

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

manual.manticoresearch.com

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

www.sqlite.org/docs.html

Developer

Andrey Gershun & Mathias R. Wulff

Manticore Software

Snowflake Computing Inc.

Dwayne Richard Hipp

Initial release

2014

2017

2014

since 2012, originally named StormDB

2014

2000

Current release

6.0, February 2023

10 R1, October 2018

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

GPL version 2

Open Source

Mozilla public license

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C++

Server operating systems

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

FreeBSD
Linux
macOS
Windows

Linux
macOS

hosted

server-less

Data scheme

schema-free

Fixed schema

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

dynamic column types

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

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

SQL-like query language

yes

distributed, parallel query execution

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

JavaScript

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

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

user defined functions

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate 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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

The original contents of fields are not stored in the Manticore index.

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 rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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