DBMS > Amazon Redshift vs. BigObject vs. Manticore Search vs. VoltDB

System Properties Comparison Amazon Redshift vs. BigObject vs. Manticore Search vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

aws.amazon.com/redshift

bigobject.io

manticoresearch.com

www.voltdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

manual.manticoresearch.com

docs.voltdb.com

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Manticore Software

VoltDB Inc.

Initial release

2012

2015

2017

2010

Current release

6.0, February 2023

11.3, April 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPL version 2

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java, C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
macOS
Windows

Linux
OS X

for development

Data scheme

yes

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 DML and DDL statements

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

user defined functions

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

FOREIGN KEY constraints are not supported

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

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

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