DBMS > BigchainDB vs. Manticore Search vs. MonetDB vs. SwayDB vs. TimesTen

System Properties Comparison BigchainDB vs. Manticore Search vs. MonetDB vs. SwayDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

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

A relational database management system that stores data in columns

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

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

Technical documentation

bigchaindb.readthedocs.io/en/latest

manual.manticoresearch.com

www.monetdb.org/Documentation

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Manticore Software

MonetDB BV

Simer Plaha

Oracle

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

Initial release

2016

2017

2004

2018

1998

Current release

6.0, February 2023

Dec2023 (11.49), December 2023

Release 22.1

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

GPL version 2

Open Source

Mozilla Public License 2.0

Open Source

GNU Affero GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Python

C++

Scala

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

Fixed schema

yes

schema-free

yes

Typing

predefined data types such as float or date

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

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

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

Java
Kotlin
Scala

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

user defined functions

yes, in SQL, C, R

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication based on Galera library

none

Source-replica replication available in experimental status

none

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

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Atomic execution of operations

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

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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More resources

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