DBMS > Google Cloud Bigtable vs. Oracle NoSQL vs. Stardog vs. Vitess

System Properties Comparison Google Cloud Bigtable vs. Oracle NoSQL vs. Stardog vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Key-value store
Wide column store

Document store
Key-value store
Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

cloud.google.com/bigtable

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

www.stardog.com

vitess.io

Technical documentation

cloud.google.com/bigtable/docs

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

docs.stardog.com

vitess.io/docs

Developer

Google

Oracle

Stardog-Union

The Linux Foundation, PlanetScale

Initial release

2015

2011

2010

2013

Current release

24.1, May 2024

7.3.0, May 2020

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

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

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache Version 2.0, commercial licenses available

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
Solaris SPARC/x86

Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

schema-free

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

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

optional

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

with proprietary extensions

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

yes

proprietary syntax

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

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

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency in HA-Cluster

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-row operations

configurable

ACID within a storage node (=shard)

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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More resources

Recent citations in the news

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31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
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Google Cloud makes it cheaper to run smaller workloads on Bigtable
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With Vitess 4.0, database vendor matures cloud-native platform
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provided by Google News

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