DBMS > EXASOL vs. HEAVY.AI vs. JanusGraph vs. OrientDB vs. Snowflake

System Properties Comparison EXASOL vs. HEAVY.AI vs. JanusGraph vs. OrientDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Relational DBMS

Graph DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.exasol.com

github.com/heavyai/heavydb
www.heavy.ai

janusgraph.org

orientdb.org

www.snowflake.com

Technical documentation

www.exasol.com/resources

docs.heavy.ai

docs.janusgraph.org

www.orientdb.com/docs/last/index.html

docs.snowflake.net/manuals/index.html

Developer

Exasol

HEAVY.AI, Inc.

Linux Foundation; originally developed as Titan by Aurelius

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

Initial release

2000

2016

2017

2010

2014

Current release

5.10, January 2022

0.6.3, February 2023

3.2.29, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Apache version 2

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++ and CUDA

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

All OS with a Java JDK (>= JDK 6)

hosted

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

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

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

SQL

Support of SQL

yes

SQL-like query language, no joins

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
Thrift
Vega

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

All languages supporting JDBC/ODBC/Thrift
Python

Clojure
Java
Python

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

Java, Javascript

user defined functions

Triggers

yes

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

via Faunus, a graph analytics engine

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationship in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

Access rights for users and roles; record level security configurable

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

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