DBMS > Alibaba Cloud AnalyticDB for MySQL vs. GridGain vs. HBase vs. Milvus vs. Snowflake

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. GridGain vs. HBase vs. Milvus vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

GridGain is an in-memory computing platform, built on Apache Ignite

Wide-column store based on Apache Hadoop and on concepts of BigTable

A DBMS designed for efficient storage of vector data and vector similarity searches

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Wide column store

Vector DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.alibabacloud.com/product/analyticdb-for-mysql

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

www.gridgain.com/docs/index.html

hbase.apache.org/book.html

milvus.io/docs/overview.md

docs.snowflake.net/manuals/index.html

Developer

Alibaba

GridGain Systems, Inc.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Snowflake Computing Inc.

Initial release

2007

2008

2019

2014

Current release

GridGain 8.5.1

2.3.4, January 2021

2.3.4, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java, C++, .Net

Java

C++, Go

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
Unix
Windows

using Cygwin

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

hosted

Data scheme

yes

schema-free, schema definition possible

yes

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

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

Vector, Numeric and String

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

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C#
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Groovy
Java
PHP
Python
Scala

C++
Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

yes

Coprocessors in Java

user defined functions

Triggers

yes

yes (cache interceptors and events)

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes (replicated cache)

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Role based access control and fine grained access rights

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

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
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Milvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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