DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. Tarantool vs. Yaacomo vs. YottaDB

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. Tarantool vs. Yaacomo vs. YottaDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Large scale data warehouse service for use with business intelligence tools

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store
Key-value store

Document store
Key-value store
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

Relational DBMS

using the Octo plugin

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

aws.amazon.com/redshift

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.tarantool.io

yaacomo.com

yottadb.com

Technical documentation

docs.aws.amazon.com/redshift

www.tarantool.io/en/doc

yottadb.com/resources/documentation

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

Q2WEB GmbH

YottaDB, LLC

Initial release

2012

2016

2008

2009

2001

Current release

1703

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

commercial

Open Source

AGPL 3.0

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

Java

C and C++

Server operating systems

hosted

Linux

BSD
Linux
macOS

Android
Linux
Windows

Docker
Linux

Data scheme

yes

Schema and schema-less with LDAP views

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Full-featured ANSI SQL support

yes

by using the Octo plugin

APIs and other access methods

JDBC
ODBC

LDAP

Open binary protocol

JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Source-replica replication

yes

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

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

yes, write ahead logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, full featured in-memory storage engine with persistence

yes

User concepts

Access control

fine grained access rights according to SQL-standard

LDAP bind authentication

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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