DBMS > Amazon DynamoDB vs. Couchbase vs. Datomic vs. LevelDB vs. RRDtool

System Properties Comparison Amazon DynamoDB vs. Couchbase vs. Datomic vs. LevelDB vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Document store
Key-value store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	71.85
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	17.10
Rank	#34	Overall
	#5	Document stores

Score	1.50
Rank	#148	Overall
	#68	Relational DBMS

Score	2.39
Rank	#110	Overall
	#18	Key-value stores

Score	1.68
Rank	#137	Overall
	#11	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.couchbase.com

www.datomic.com

github.com/google/leveldb

oss.oetiker.ch/rrdtool

Technical documentation

docs.aws.amazon.com/dynamodb

docs.couchbase.com

docs.datomic.com

github.com/google/leveldb/blob/main/doc/index.md

oss.oetiker.ch/rrdtool/doc

Developer

Amazon

Couchbase, Inc.

Cognitect

Google

Tobias Oetiker

Initial release

2012

2011

2012

2011

1999

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.0.7180, July 2024

1.23, February 2021

1.8.0, 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

limited edition free

Open Source

BSD

Open Source

GPL V2 and FLOSS

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, C++, Go and Erlang

Java, Clojure

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Illumos
Linux
OS X
Windows

HP-UX
Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP API

in-process shared library
Pipes

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Clojure
Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Transaction Functions

Triggers

yes

by integration with AWS Lambda

yes

via the TAP protocol

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

none

But extensive use of caching in the application peers

none

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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

none

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

by using the rrdcached daemon

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes

Ephemeral buckets

yes

recommended only for testing and development

yes

User concepts

Access control

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

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

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