DBMS > Alibaba Cloud MaxCompute vs. Badger vs. Brytlyt vs. Snowflake vs. TimescaleDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Badger vs. Brytlyt vs. Snowflake vs. TimescaleDB

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Cloud-based data warehousing service for structured and semi-structured data

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

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

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

github.com/dgraph-io/badger

brytlyt.io

www.snowflake.com

www.timescale.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

godoc.org/github.com/dgraph-io/badger

docs.brytlyt.io

docs.snowflake.net/manuals/index.html

docs.timescale.com

Developer

Alibaba

DGraph Labs

Brytlyt

Snowflake Computing Inc.

Timescale

Initial release

2016

2017

2016

2014

2017

Current release

5.0, August 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 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

C, C++ and CUDA

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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.

yes

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

Fluentd
Flume
MaxCompute Console

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in PL/pgSQL

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Source-replica replication

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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