DBMS > Atos Standard Common Repository vs. ReductStore vs. Rockset vs. Tarantool

System Properties Comparison Atos Standard Common Repository vs. ReductStore vs. Rockset vs. Tarantool

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Editorial information provided by DB-Engines

Name

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

Description

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

Primary database model

Document store
Key-value store

Time Series DBMS

Document store

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS
Search engine

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

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

Website

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

github.com/reductstore
www.reduct.store

rockset.com

www.tarantool.io

Technical documentation

www.reduct.store/docs

docs.rockset.com

www.tarantool.io/en/doc

Developer

Atos Convergence Creators

ReductStore LLC

Rockset

Initial release

2016

2023

2019

2008

Current release

1703

1.9, March 2024

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

commercial

Open Source

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

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++, Rust

C++

C and C++

Server operating systems

Linux

Docker
Linux
macOS
Windows

hosted

BSD
Linux
macOS

Data scheme

Schema and schema-less with LDAP views

schema-free

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

Typing

predefined data types such as float or date

optional

dynamic typing

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

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

Read-only SQL queries, including JOINs

Full-featured ANSI SQL support

APIs and other access methods

LDAP

HTTP API

HTTP REST

Open binary protocol

Supported programming languages

All languages with LDAP bindings

C++
JavaScript (Node.js)
Python
Rust

Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

Lua, C and SQL stored procedures

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic sharding

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

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)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

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

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

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

User concepts

Access control

LDAP bind authentication

Access rights for users and organizations can be defined via Rockset console

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

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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