DBMS > AlaSQL vs. HarperDB vs. Manticore Search vs. RDF4J vs. Sadas Engine

System Properties Comparison AlaSQL vs. HarperDB vs. Manticore Search vs. RDF4J vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

docs.harperdb.io/docs

manual.manticoresearch.com

rdf4j.org/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Andrey Gershun & Mathias R. Wulff

HarperDB

Manticore Software

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

SADAS s.r.l.

Initial release

2014

2017

2004

2006

Current release

3.1, August 2021

6.0, February 2023

8.0

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community edition available

Open Source

GPL version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free trial version available

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.

Implementation language

JavaScript

Node.js

C++

Java

C++

Server operating systems

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

Linux
OS X

FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

AIX
Linux
Windows

Data scheme

schema-free

dynamic schema

Fixed schema

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

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.

Can index from XML

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 data manipulation statements

SQL-like query language

yes

APIs and other access methods

JavaScript API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC
Proprietary protocol

Supported programming languages

JavaScript

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Java
PHP
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

the nodes on which a table resides can be defined

Synchronous replication based on Galera library

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

Atomic execution of specific operations

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes, using LMDB

yes

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

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

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