DBMS > AgensGraph vs. Alibaba Cloud MaxCompute vs. Apache Druid vs. Snowflake

System Properties Comparison AgensGraph vs. Alibaba Cloud MaxCompute vs. Apache Druid vs. Snowflake

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

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

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

bitnine.net/agensgraph

www.alibabacloud.com/product/maxcompute

druid.apache.org

www.snowflake.com

Technical documentation

bitnine.net/documentation

www.alibabacloud.com/help/en/maxcompute

druid.apache.org/docs/latest/design

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Alibaba

Apache Software Foundation and contributors

Snowflake Computing Inc.

Initial release

2016

2012

2014

Current release

2.1, December 2018

29.0.1, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Apache license v2

commercial

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

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Unix

hosted

Data scheme

depending on used data model

yes

schema-less columns are supported

yes

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

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

SQL for querying

yes

APIs and other access methods

Cypher Query Language
JDBC

Fluentd
Flume
MaxCompute Console

JDBC
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

Java

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

in Java

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Implicit feature of the cloud service

Sharding

manual/auto, time-based

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

yes, via HDFS, S3 or other storage engines

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

fine grained access rights according to SQL-standard

Access rights for users and roles

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.