DBMS > Amazon DynamoDB vs. Hypertable vs. KeyDB vs. mSQL vs. RavenDB

System Properties Comparison Amazon DynamoDB vs. Hypertable vs. KeyDB vs. mSQL vs. RavenDB

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

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

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

mSQL (Mini SQL) is a simple and lightweight RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store
Key-value store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/dynamodb

github.com/Snapchat/KeyDB
keydb.dev

hughestech.com.au/products/msql

ravendb.net

Technical documentation

docs.aws.amazon.com/dynamodb

docs.keydb.dev

ravendb.net/docs

Developer

Amazon

Hypertable Inc.

EQ Alpha Technology Ltd.

Hughes Technologies

Hibernating Rhinos

Initial release

2012

2009

2019

1994

2010

Current release

0.9.8.11, March 2016

4.4, October 2021

5.4, July 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU version 3. Commercial license available

Open Source

BSD-3

commercial

free licenses can be provided

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

yes

by using the Redis Search module

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP API

C++ API
Thrift

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

Multi-source replication
Source-replica replication

none

Multi-source replication

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

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

none

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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)

simple password-based access control and ACL

Authorization levels configured per client per database

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