DBMS > Alibaba Cloud MaxCompute vs. Amazon SimpleDB vs. KairosDB vs. KeyDB vs. ObjectBox

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon SimpleDB vs. KairosDB vs. KeyDB vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

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

Distributed Time Series DBMS based on Cassandra or H2

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

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Secondary database models

Time Series DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/simpledb

github.com/kairosdb/kairosdb

github.com/Snapchat/KeyDB
keydb.dev

objectbox.io

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/simpledb

kairosdb.github.io

docs.keydb.dev

docs.objectbox.io

Developer

Alibaba

Amazon

EQ Alpha Technology Ltd.

ObjectBox Limited

Initial release

2016

2007

2013

2019

2017

Current release

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD-3

Open Source

Apache License 2.0

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

Java

C++

C and C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Android
iOS
Linux
macOS
Windows

Data scheme

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

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

by using the Redis Search module

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary native API

Supported programming languages

Java

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

Java
JavaScript

Node.js
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++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

user defined functions

in Java

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding must be implemented in the application

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

Optimistic locking, atomic execution of commands blocks and scripts

ACID

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

simple password-based access control

simple password-based access control and ACL

yes

More information provided by the system vendor

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