DBMS > Amazon DocumentDB vs. etcd vs. Hypertable

System Properties Comparison Amazon DocumentDB vs. etcd vs. Hypertable

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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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

A distributed reliable key-value store

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

Primary database model

Document store

Key-value store

Wide column store

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

Score	1.89
Rank	#137	Overall
	#24	Document stores

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Website

aws.amazon.com/documentdb

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

Technical documentation

aws.amazon.com/documentdb/resources

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

Developer

Hypertable Inc.

Initial release

2019

2009

Current release

3.4, August 2019

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

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++

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

Linux
OS X
Windows

an inofficial Windows port is available

Data scheme

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

gRPC
JSON over HTTP

C++ API
Thrift

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

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

selectable replication factor on file system level

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

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

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.

User concepts

Access control

Access rights for users and roles

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