DBMS > Google Cloud Bigtable vs. RethinkDB vs. Stardog vs. SwayDB vs. SWC-DB

System Properties Comparison Google Cloud Bigtable vs. RethinkDB vs. Stardog vs. SwayDB vs. SWC-DB

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.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store
Wide column store

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cloud.google.com/bigtable

rethinkdb.com

www.stardog.com

swaydb.simer.au

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cloud.google.com/bigtable/docs

rethinkdb.com/docs

docs.stardog.com

Developer

Google

The Linux Foundation

since July 2017

Stardog-Union

Simer Plaha

Alex Kashirin

Initial release

2015

2009

2010

2018

2020

Current release

2.4.1, August 2020

7.3.0, May 2020

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

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

Open Source

GNU Affero GPL V3.0

Open Source

GPL V3

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++

Java

Scala

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Windows

Linux

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

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

SQL-like query language

APIs and other access methods

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

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

Proprietary protocol
Thrift

Supported programming languages

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Java
Kotlin
Scala

C++

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Client-side triggers through changefeeds

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

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

Source-replica replication

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Atomic single-row operations

Atomic single-document operations

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

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

User concepts

Access control

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

yes

users and table-level permissions

Access rights for users and roles

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More resources

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