DBMS > Atos Standard Common Repository vs. Drizzle vs. InfinityDB vs. Riak TS vs. Rockset

System Properties Comparison Atos Standard Common Repository vs. Drizzle vs. InfinityDB vs. Riak TS vs. Rockset

Editorial information provided by DB-Engines

Name

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

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A Java embedded Key-Value Store which extends the Java Map interface

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

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

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS
Search engine

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

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

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

boilerbay.com

rockset.com

Technical documentation

boilerbay.com/infinitydb/manual

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

docs.rockset.com

Developer

Atos Convergence Creators

Drizzle project, originally started by Brian Aker

Boiler Bay Inc.

Open Source, formerly Basho Technologies

Rockset

Initial release

2016

2008

2002

2015

2019

Current release

1703

7.2.4, September 2012

4.0

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

Open Source

commercial

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++

Java

Erlang

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
OS X

hosted

Data scheme

Schema and schema-less with LDAP views

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

optional

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

dynamic typing

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

manual creation possible, using inversions based on multi-value capability

restricted

all fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

yes, limited

Read-only SQL queries, including JOINs

APIs and other access methods

LDAP

JDBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

All languages with LDAP bindings

C
C++
Java
PHP

Java

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)
Python

Server-side scripts

Stored procedures

Erlang

Triggers

yes

hooks for callbacks inside the server can be used.

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

links between datasets can be stored

Transaction concepts

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

Atomic execution of specific operations

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

LDAP bind authentication

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

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