DBMS > Amazon Redshift vs. BigchainDB vs. Manticore Search vs. TimesTen vs. Vitess

System Properties Comparison Amazon Redshift vs. BigchainDB vs. Manticore Search vs. TimesTen vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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

In-Memory RDBMS compatible to Oracle

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

aws.amazon.com/redshift

www.bigchaindb.com

manticoresearch.com

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

vitess.io

Technical documentation

docs.aws.amazon.com/redshift

bigchaindb.readthedocs.io/en/latest

manual.manticoresearch.com

docs.oracle.com/database/timesten-18.1

vitess.io/docs

Developer

Amazon (based on PostgreSQL)

Manticore Software

Oracle, TimesTen Performance Software, HP

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

The Linux Foundation, PlanetScale

Initial release

2012

2016

2017

1998

2013

Current release

6.0, February 2023

11 Release 2 (11.2.2.8.0)

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

GPL version 2

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Python

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
macOS
Windows

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

Docker
Linux
macOS

Data scheme

yes

schema-free

Fixed schema

yes

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

Secondary indexes

restricted

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

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

C
C++
Java
PL/SQL

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

user defined functions

in Python

user defined functions

PL/SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Synchronous replication based on Galera library

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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

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

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

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

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

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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