DBMS > Alibaba Cloud MaxCompute vs. Amazon SimpleDB vs. BigObject vs. GreptimeDB vs. ToroDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Amazon SimpleDB vs. BigObject vs. GreptimeDB vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

Analytic DBMS for real-time computations and queries

An open source Time Series DBMS built for increased scalability, high performance and efficiency

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

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

Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Document store

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

Score	0.85
Rank	#203	Overall
	#96	Relational DBMS

Score	1.89
Rank	#128	Overall
	#22	Key-value stores

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

aws.amazon.com/simpledb

bigobject.io

greptime.com

github.com/torodb/server

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.aws.amazon.com/simpledb

docs.bigobject.io

docs.greptime.com

Developer

Alibaba

Amazon

BigObject, Inc.

Greptime Inc.

8Kdata

Initial release

2016

2007

2015

2022

2016

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

Open Source

AGPL-V3

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

Rust

Java

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

gRPC
HTTP API
JDBC

Supported programming languages

Java

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

C++
Erlang
Go
Java
JavaScript

Server-side scripts

Stored procedures

user defined functions

in Java

Lua

Python

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

Source-replica replication

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

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Concurrent data updates can be detected by the application

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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.

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 rights management via user accounts

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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