DBMS > Amazon SimpleDB vs. BigchainDB vs. Dragonfly vs. Google BigQuery vs. RocksDB

System Properties Comparison Amazon SimpleDB vs. BigchainDB vs. Dragonfly vs. Google BigQuery 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

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Large scale data warehouse service with append-only tables

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

Primary database model

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

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

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

Website

aws.amazon.com/simpledb

www.bigchaindb.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

cloud.google.com/bigquery

rocksdb.org

Technical documentation

docs.aws.amazon.com/simpledb

bigchaindb.readthedocs.io/en/latest

www.dragonflydb.io/docs

cloud.google.com/bigquery/docs

github.com/facebook/rocksdb/wiki

Developer

Amazon

DragonflyDB team and community contributors

Google

Facebook, Inc.

Initial release

2007

2016

2023

2010

2013

Current release

1.0, March 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

BSL 1.1

commercial

Open Source

BSD

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

Python

C++

Server operating systems

hosted

Linux

hosted

Linux

Data scheme

schema-free

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

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

Go
Haskell
Java
JavaScript
Python
Ruby

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Lua

user defined functions

in JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

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

Eventual Consistency

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

Atomic execution of command blocks and scripts

Since BigQuery is designed for querying data

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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)

yes

Password-based authentication

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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