DBMS > BigchainDB vs. EXASOL vs. IRONdb vs. JaguarDB vs. Microsoft SQL Server

System Properties Comparison BigchainDB vs. EXASOL vs. IRONdb vs. JaguarDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Performant, highly scalable DBMS for AI and IoT applications

Microsofts flagship relational DBMS

Primary database model

Document store

Relational DBMS

Time Series DBMS

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

www.bigchaindb.com

www.exasol.com

www.circonus.com/solutions/time-series-database/

www.jaguardb.com

www.microsoft.com/en-us/sql-server

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.exasol.com/resources

docs.circonus.com/irondb/category/getting-started

www.jaguardb.com/support.html

learn.microsoft.com/en-US/sql/sql-server

Developer

Exasol

Circonus LLC.

DataJaguar, Inc.

Microsoft

Initial release

2016

2000

2017

2015

1989

Current release

V0.10.20, January 2018

3.3 July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

GPL V3.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Python

C and C++

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL

Support of SQL

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

CLI Client
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Java
Lua
Python
R

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

configurable replication factor, datacenter aware

Multi-source replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

User concepts

Access control

yes

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

rights management via user accounts

fine grained access rights according to SQL-standard

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