DBMS > AlaSQL vs. BigchainDB vs. BigObject vs. Elasticsearch vs. MySQL

System Properties Comparison AlaSQL vs. BigchainDB vs. BigObject vs. Elasticsearch vs. MySQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Analytic DBMS for real-time computations and queries

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Widely used open source RDBMS

Primary database model

Document store
Relational DBMS

Document store

Relational DBMS

a hierachical model (tree) can be imposed

Search engine

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
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	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

alasql.org

www.bigchaindb.com

bigobject.io

www.elastic.co/elasticsearch

www.mysql.com

Technical documentation

github.com/AlaSQL/alasql

bigchaindb.readthedocs.io/en/latest

docs.bigobject.io

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

dev.mysql.com/doc

Developer

Andrey Gershun & Mathias R. Wulff

BigObject, Inc.

Elastic

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

2016

2015

2010

1995

Current release

8.6, January 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

AGPL v3

commercial

free community edition available

Open Source

Elastic License

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

JavaScript

Python

Java

C and C++

Server operating systems

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

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

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

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

SQL-like DML and DDL statements

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JavaScript API

CLI Client
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

not for MyISAM storage engine

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

yes

Memcached and Redis integration

yes

User concepts

Access control

yes

Users with fine-grained authorization concept

no user groups or roles

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