DBMS > EXASOL vs. HugeGraph vs. JaguarDB vs. Snowflake vs. VoltDB

System Properties Comparison EXASOL vs. HugeGraph vs. JaguarDB vs. Snowflake vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

Performant, highly scalable DBMS for AI and IoT applications

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Graph DBMS

Key-value store
Vector DBMS

Relational DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

www.exasol.com

github.com/hugegraph
hugegraph.apache.org

www.jaguardb.com

www.snowflake.com

www.voltdb.com

Technical documentation

www.exasol.com/resources

hugegraph.apache.org/docs

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

docs.voltdb.com

Developer

Exasol

Baidu

DataJaguar, Inc.

Snowflake Computing Inc.

VoltDB Inc.

Initial release

2000

2018

2015

2014

2010

Current release

0.9

3.3 July 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

the server part. Clients available in other languages

Java, C++

Server operating systems

Linux
macOS
Unix

Linux

hosted

Linux
OS X

for development

Data scheme

yes

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

yes

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

only a subset of SQL 99

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC

CLI Client
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java
Lua
Python
R

Groovy
Java
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

user defined functions

Java

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication

yes

Multi-source replication
Source-replica replication

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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, groups and roles according to SQL-standard

Users, roles and permissions

rights management via user accounts

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

Users and roles with access to stored procedures

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