DBMS > CouchDB vs. EXASOL vs. HugeGraph vs. Snowflake vs. TerarkDB

System Properties Comparison CouchDB vs. EXASOL vs. HugeGraph vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A fast-speed and highly-scalable Graph DBMS

Cloud-based data warehousing service for structured and semi-structured data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	10.26
Rank	#45	Overall
	#7	Document stores

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

couchdb.apache.org

www.exasol.com

github.com/hugegraph
hugegraph.apache.org

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

docs.couchdb.org/en/stable

www.exasol.com/resources

hugegraph.apache.org/docs

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Exasol

Baidu

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2005

2000

2018

2014

2016

Current release

3.3.3, December 2023

0.9

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Java

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Unix

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

via views

yes

also supports composite index and range index

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

.Net
JDBC
ODBC
WebSocket

Java API
RESTful HTTP API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Java
Lua
Python
R

Groovy
Java
Python

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

asynchronous Gremlin script jobs

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

Users, roles and permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

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