DBMS > Alibaba Cloud MaxCompute vs. Elasticsearch vs. JanusGraph vs. Percona Server for MongoDB vs. Snowflake

System Properties Comparison Alibaba Cloud MaxCompute vs. Elasticsearch vs. JanusGraph vs. Percona Server for MongoDB vs. Snowflake

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

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

Primary database model

Relational DBMS

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

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

www.elastic.co/elasticsearch

janusgraph.org

www.percona.com/mongodb/software/percona-server-for-mongodb

www.snowflake.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.janusgraph.org

docs.percona.com/percona-distribution-for-mongodb

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Elastic

Linux Foundation; originally developed as Titan by Aurelius

Percona

Snowflake Computing Inc.

Initial release

2016

2010

2017

2015

2014

Current release

8.6, January 2023

0.6.3, February 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

Apache 2.0

Open Source

GPL Version 2

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

C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux

hosted

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

schema-free

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Java API
RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Supported programming languages

Java

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Java

yes

JavaScript

user defined functions

Triggers

yes

by using the 'percolation' feature

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Memcached and Redis integration

yes

via In-Memory Engine

User concepts

Access control

Access rights for users and roles

User authentification and security via Rexster Graph Server

Access rights for users and roles

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

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