DBMS > BigchainDB vs. EJDB vs. Microsoft SQL Server vs. MonetDB vs. TimesTen

System Properties Comparison BigchainDB vs. EJDB vs. Microsoft SQL Server vs. MonetDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.bigchaindb.com

github.com/Softmotions/ejdb

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

www.monetdb.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

github.com/Softmotions/ejdb/blob/master/README.md

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

www.monetdb.org/Documentation

docs.oracle.com/database/timesten-18.1

Developer

Softmotions

Microsoft

MonetDB BV

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2012

1989

2004

1998

Current release

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

GPLv2

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Python

C++

Server operating systems

Linux

server-less

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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 2003 with some extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

in-process shared library

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

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

yes, in SQL, C, R

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

by means of logfiles and checkpoints

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

fine grained access rights according to SQL-standard

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