DBMS > Amazon DynamoDB vs. EXASOL vs. Hive vs. KeyDB vs. SiriDB

System Properties Comparison Amazon DynamoDB vs. EXASOL vs. Hive vs. KeyDB vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Open Source Time Series DBMS

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

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	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

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

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.exasol.com

hive.apache.org

github.com/Snapchat/KeyDB
keydb.dev

siridb.com

Technical documentation

docs.aws.amazon.com/dynamodb

www.exasol.com/resources

cwiki.apache.org/confluence/display/Hive/Home

docs.keydb.dev

docs.siridb.com

Developer

Amazon

Exasol

Apache Software Foundation

initially developed by Facebook

EQ Alpha Technology Ltd.

Cesbit

Initial release

2012

2000

2012

2019

2017

Current release

3.1.3, April 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2

Open Source

BSD-3

Open Source

MIT License

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

C++

Server operating systems

hosted

All OS with a Java VM

Linux

Data scheme

schema-free

yes

schema-free

yes

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

Numeric data

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
Thrift

Proprietary protocol

RESP - REdis Serialization Protoco

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
Lua
Python
R

C++
Java
PHP
Python

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++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

Lua

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Hadoop integration

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

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)

Access rights for users, groups and roles according to SQL-standard

Access rights for users, groups and roles

simple password-based access control and ACL

simple rights management via user accounts

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