DBMS > Amazon SimpleDB vs. BigchainDB vs. CrateDB vs. etcd vs. RocksDB

System Properties Comparison Amazon SimpleDB vs. BigchainDB vs. CrateDB vs. etcd 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

Distributed Database based on Lucene

A distributed reliable key-value store

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

Primary database model

Key-value store

Document store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Key-value store

Secondary database models

Relational DBMS

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	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

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

Website

aws.amazon.com/simpledb

www.bigchaindb.com

cratedb.com

etcd.io
github.com/etcd-io/etcd

rocksdb.org

Technical documentation

docs.aws.amazon.com/simpledb

bigchaindb.readthedocs.io/en/latest

cratedb.com/docs

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

github.com/facebook/rocksdb/wiki

Developer

Amazon

Crate

Facebook, Inc.

Initial release

2007

2016

2013

Current release

3.4, August 2019

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

Apache Version 2.0

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Python

Java

C++

Server operating systems

hosted

Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

FreeBSD
Linux
Windows

experimental

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

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

yes, but no triggers and constraints, and PostgreSQL compatibility

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

gRPC
JSON over HTTP

C++ API
Java API

Supported programming languages

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

Go
Haskell
Java
JavaScript
Python
Ruby

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions (Javascript)

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Configurable replication on table/partition-level

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

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
Read-after-write consistency on record level

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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)

yes

rights management via user accounts

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more

Licensing and pricing models

See CrateDB pricing >
» more

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