DBMS > BigchainDB vs. EXASOL vs. Manticore Search vs. Microsoft SQL Server vs. OrientDB

System Properties Comparison BigchainDB vs. EXASOL vs. Manticore Search vs. Microsoft SQL Server vs. OrientDB

Editorial information provided by DB-Engines

Name

Description

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

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

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

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Graph DBMS
Key-value store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Graph DBMS
Spatial DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Website

www.bigchaindb.com

www.exasol.com

manticoresearch.com

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

orientdb.org

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.exasol.com/resources

manual.manticoresearch.com

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

www.orientdb.com/docs/last/index.html

Developer

Exasol

Manticore Software

Microsoft

OrientDB LTD; CallidusCloud; SAP

Initial release

2016

2000

2017

1989

2010

Current release

6.0, February 2023

SQL Server 2022, November 2022

3.2.29, March 2024

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

GPL version 2

commercial

restricted free version is available

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

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Implementation language

Python

C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

schema-free

yes

Fixed schema

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

Typing

predefined data types such as float or date

yes

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

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-like query language, no joins

APIs and other access methods

CLI Client
RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

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

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Java
Lua
Python
R

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

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

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

Java, Javascript

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication based on Galera library

yes, but depending on the SQL-Server Edition

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

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

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

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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