DBMS > Amazon Redshift vs. Manticore Search vs. OrigoDB vs. Riak TS vs. YDB

System Properties Comparison Amazon Redshift vs. Manticore Search vs. OrigoDB vs. Riak TS vs. YDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A fully ACID in-memory object graph database

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Search engine

Document store
Object oriented DBMS

Time Series DBMS

Document store
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	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

aws.amazon.com/redshift

manticoresearch.com

origodb.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.aws.amazon.com/redshift

manual.manticoresearch.com

origodb.com/docs

www.tiot.jp/riak-docs/riak/ts/latest

ydb.tech/en/docs

Developer

Amazon (based on PostgreSQL)

Manticore Software

Robert Friberg et al

Open Source, formerly Basho Technologies

Yandex

Initial release

2012

2017

2009

under the name LiveDB

2015

2019

Current release

6.0, February 2023

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Apache 2.0; commercial license 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

C++

Erlang

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

Linux
Windows

Linux
OS X

Linux

Data scheme

yes

Fixed schema

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

restricted

yes

full-text index on all search fields

yes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes, limited

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

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

.NET Client API
HTTP API
LINQ

HTTP API
Native Erlang Interface

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Erlang

Triggers

yes

Domain Events

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

Source-replica replication

selectable replication factor

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

depending on model

links between datasets can be stored

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

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

yes

Write ahead log

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

Role based authorization

Access rights defined for Yandex Cloud users

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