DBMS > Apache Drill vs. Atos Standard Common Repository vs. CockroachDB vs. Postgres-XL

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. CockroachDB vs. Postgres-XL

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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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	4.74
Rank	#67	Overall
	#36	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

drill.apache.org

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

www.cockroachlabs.com

www.postgres-xl.org

Technical documentation

drill.apache.org/docs

www.cockroachlabs.com/docs

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Atos Convergence Creators

Cockroach Labs

Initial release

2012

2016

2015

2014

since 2012, originally named StormDB

Current release

1.20.3, January 2023

1703

24.1.0, May 2024

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0, commercial license available

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS
Windows

Linux
macOS

Data scheme

schema-free

Schema and schema-less with LDAP views

dynamic schema

yes

Typing

predefined data types such as float or date

yes

optional

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes, wire compatible with PostgreSQL

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

LDAP

JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C++

All languages with LDAP bindings

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

LDAP bind authentication

Role-based access control

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
27 September 2019, Towards Data Science

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, businesswire.com

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

Cockroach Labs shakes up its licensing to force bigger companies to pay
15 August 2024, TechCrunch

CockroachDB scuttles away from open source Core offering
19 August 2024, The Register

CockroachDB retires self-hosted Core offering, makes Enterprise version free for companies under $10M in annual revenue
15 August 2024, SDTimes.com

Cockroach Labs Deepens Partnership with Google Cloud, CockroachDB Selected to Join Google Distributed Cloud
9 April 2024, PR Newswire

Now CockroachDB Ditches Open-Source License
20 August 2024, It's FOSS News

provided by Google News

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