DBMS > EXASOL vs. Google BigQuery vs. JanusGraph vs. jBASE

System Properties Comparison EXASOL vs. Google BigQuery vs. JanusGraph vs. jBASE

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

A Graph DBMS optimized for distributed clusters

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

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Relational DBMS

Graph DBMS

Multivalue DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

www.exasol.com

cloud.google.com/bigquery

janusgraph.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

www.exasol.com/resources

cloud.google.com/bigquery/docs

docs.janusgraph.org

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Exasol

Google

Linux Foundation; originally developed as Titan by Aurelius

Rocket Software (formerly Zumasys)

Initial release

2000

2010

2017

1991

Current release

0.6.3, February 2023

5.7

License

Commercial or Open Source

commercial

Open Source

Apache 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

Java

Server operating systems

hosted

Linux
OS X
Unix
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

Embedded SQL for jBASE in BASIC

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Clojure
Java
Python

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying 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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

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