DBMS > Google BigQuery vs. Immudb vs. JanusGraph vs. Oracle Coherence

System Properties Comparison Google BigQuery vs. Immudb vs. JanusGraph vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

A Graph DBMS optimized for distributed clusters

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

Oracles in-memory data grid solution

Primary database model

Secondary database models

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

cloud.google.com/bigquery

github.com/codenotary/immudb
immudb.io

janusgraph.org

www.oracle.com/java/coherence

Technical documentation

cloud.google.com/bigquery/docs

docs.immudb.io

docs.janusgraph.org

docs.oracle.com/en/middleware/standalone/coherence

Developer

Google

Codenotary

Linux Foundation; originally developed as Titan by Aurelius

Oracle

Initial release

2010

2020

2017

2007

Current release

1.2.3, April 2022

0.6.3, February 2023

14.1, August 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
OS X
Unix
Windows

All OS with a Java VM

Data scheme

yes

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

yes

SQL-like syntax

APIs and other access methods

RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Since BigQuery is designed for querying data

ACID

configurable

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

optionally

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

Google Cloud Identity & Access Management (IAM)

User authentification and security via Rexster Graph Server

authentification to access the cache via certificates or http basic authentication

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