DBMS > Apache Drill vs. Atos Standard Common Repository vs. BigchainDB vs. LMDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. BigchainDB vs. LMDB vs. Microsoft Azure Cosmos DB

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

A high performant, light-weight, embedded key-value database library

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Document store

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	2.33
Rank	#118	Overall
	#21	Key-value stores

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

drill.apache.org

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

www.bigchaindb.com

www.symas.com/symas-embedded-database-lmdb

azure.microsoft.com/services/cosmos-db

Technical documentation

drill.apache.org/docs

bigchaindb.readthedocs.io/en/latest

www.lmdb.tech/doc

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation

Atos Convergence Creators

Symas

Microsoft

Initial release

2012

2016

2011

2014

Current release

1.20.3, January 2023

1703

0.9.32, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

AGPL v3

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

Server operating systems

Linux
OS X
Windows

Linux

Linux
Unix
Windows

hosted

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

JSON types

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

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

LDAP

CLI Client
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

C++

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

yes,with MongoDB ord RethinkDB

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

yes

Access rights can be defined down to the item level

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