DBMS > Amazon SimpleDB vs. Google Cloud Bigtable vs. Hypertable vs. RocksDB vs. TerminusDB

System Properties Comparison Amazon SimpleDB vs. Google Cloud Bigtable vs. Hypertable vs. RocksDB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store

Key-value store
Wide column store

Wide column store

Key-value store

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

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

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/simpledb

cloud.google.com/bigtable

rocksdb.org

terminusdb.com

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/bigtable/docs

github.com/facebook/rocksdb/wiki

terminusdb.github.io/terminusdb/#

Developer

Amazon

Google

Hypertable Inc.

Facebook, Inc.

DataChemist Ltd.

Initial release

2007

2015

2009

2013

2018

Current release

0.9.8.11, March 2016

9.2.1, May 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

BSD

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Prolog, Rust

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

yes

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

All columns are indexed automatically

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP API

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

C++ API
Thrift

C++ API
Java API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

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

C++
Java
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

horizontal partitioning

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor on file system level

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

Atomic single-row operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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 and roles can be defined via the AWS Identity and Access Management (IAM)

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

Role-based access control

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