DBMS > AlaSQL vs. Atos Standard Common Repository vs. etcd vs. Google BigQuery vs. Manticore Search

System Properties Comparison AlaSQL vs. Atos Standard Common Repository vs. etcd vs. Google BigQuery vs. Manticore Search

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

JavaScript DBMS library

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A distributed reliable key-value store

Large scale data warehouse service with append-only tables

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

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Key-value store

Relational DBMS

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

alasql.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

etcd.io
github.com/etcd-io/etcd

cloud.google.com/bigquery

manticoresearch.com

Technical documentation

github.com/AlaSQL/alasql

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

cloud.google.com/bigquery/docs

manual.manticoresearch.com

Developer

Andrey Gershun & Mathias R. Wulff

Atos Convergence Creators

Google

Manticore Software

Initial release

2014

2016

2010

2017

Current release

1703

3.4, August 2019

6.0, February 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2

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

Java

C++

Server operating systems

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

Linux

FreeBSD
Linux
Windows

experimental

hosted

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

yes

Fixed schema

Typing

predefined data types such as float or date

optional

yes

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

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

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

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

yes

SQL-like query language

APIs and other access methods

JavaScript API

LDAP

gRPC
JSON over HTTP

RESTful HTTP/JSON API

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

Supported programming languages

JavaScript

All languages with LDAP bindings

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

Triggers

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

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

Since BigQuery is designed for querying data

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

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.

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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