DBMS > Google BigQuery vs. Oracle Coherence vs. Oracle NoSQL vs. Rockset

System Properties Comparison Google BigQuery vs. Oracle Coherence vs. Oracle NoSQL vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Oracles in-memory data grid solution

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Document store

Secondary database models

Relational DBMS
Search engine

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

cloud.google.com/bigquery

www.oracle.com/java/coherence

www.oracle.com/database/nosql/technologies/nosql

rockset.com

Technical documentation

cloud.google.com/bigquery/docs

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.rockset.com

Developer

Google

Oracle

Rockset

Initial release

2010

2007

2011

2019

Current release

14.1, August 2023

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

C++

Server operating systems

hosted

All OS with a Java VM

Linux
Solaris SPARC/x86

hosted

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

optional

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like DML and DDL statements

Read-only SQL queries, including JOINs

APIs and other access methods

RESTful HTTP/JSON API

JCache
JPA
RESTful HTTP API

RESTful HTTP API

HTTP REST

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with selectable consistency level

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

authentification to access the cache via certificates or http basic authentication

Access rights for users and roles

Access rights for users and organizations can be defined via Rockset console

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