DBMS > Apache Drill vs. EsgynDB vs. etcd vs. IBM Cloudant

System Properties Comparison Apache Drill vs. EsgynDB vs. etcd vs. IBM Cloudant

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Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A distributed reliable key-value store

Database as a Service offering based on Apache CouchDB

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Document store

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Website

drill.apache.org

www.esgyn.cn

etcd.io
github.com/etcd-io/etcd

www.ibm.com/products/cloudant

Technical documentation

drill.apache.org/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation

Esgyn

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2012

2015

2010

Current release

1.20.3, January 2023

3.4, August 2019

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache Version 2.0

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

C++, Java

Erlang

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
Windows

experimental

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

gRPC
JSON over HTTP

RESTful HTTP/JSON API

Supported programming languages

C++

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

View functions (Map-Reduce) in JavaScript

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

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