DBMS > Amazon DynamoDB vs. Hypertable vs. Oracle Berkeley DB vs. Rockset

System Properties Comparison Amazon DynamoDB vs. Hypertable vs. Oracle Berkeley DB vs. Rockset

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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, scalable database service by Amazon with the data stored in Amazons cloud

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

Widely used in-process key-value store

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

Primary database model

Document store
Key-value store

Wide column store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Secondary database models

Relational DBMS
Search engine

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

aws.amazon.com/dynamodb

www.oracle.com/database/technologies/related/berkeleydb.html

rockset.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.oracle.com/cd/E17076_05/html/index.html

docs.rockset.com

Developer

Amazon

Hypertable Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Rockset

Initial release

2012

2009

1994

2019

Current release

0.9.8.11, March 2016

18.1.40, May 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU version 3. Commercial license available

Open Source

commercial license available

commercial

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++

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

hosted

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

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.

yes

only with the Berkeley DB XML edition

ingestion from XML files supported

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

Read-only SQL queries, including JOINs

APIs and other access methods

RESTful HTTP API

C++ API
Thrift

HTTP REST

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

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

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

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