DBMS > Amazon SimpleDB vs. Apache Druid vs. BigchainDB vs. EventStoreDB vs. RocksDB

System Properties Comparison Amazon SimpleDB vs. Apache Druid vs. BigchainDB vs. EventStoreDB vs. RocksDB

Editorial information provided by DB-Engines

Name

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Primary database model

Key-value store

Relational DBMS
Time Series DBMS

Document store

Event Store

Key-value store

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/simpledb

Technical documentation

docs.aws.amazon.com/simpledb

druid.apache.org/docs/latest/design

bigchaindb.readthedocs.io/en/latest

developers.eventstore.com

github.com/facebook/rocksdb/wiki

Developer

Amazon

Apache Software Foundation and contributors

Event Store Limited

Facebook, Inc.

Initial release

2007

2012

2016

2012

2013

Current release

29.0.1, April 2024

21.2, February 2021

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

AGPL v3

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

C++

Server operating systems

hosted

Linux
OS X
Unix

Linux

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-less columns are supported

schema-free

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

yes

SQL

Support of SQL

SQL for querying

APIs and other access methods

RESTful HTTP API

JDBC
RESTful HTTP/JSON API

CLI Client
RESTful HTTP API

C++ API
Java API

Supported programming languages

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

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrent data updates can be detected by the application

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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)

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

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