DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon CloudSearch vs. Hawkular Metrics vs. Milvus vs. NSDb

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Amazon CloudSearch vs. Hawkular Metrics vs. Milvus vs. NSDb

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

A hosted search engine service by Amazon with the data stored in Amazons cloud

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

aws.amazon.com/cloudsearch

www.hawkular.org

milvus.io

nsdb.io

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.aws.amazon.com/cloudsearch

www.hawkular.org/hawkular-metrics/docs/user-guide

milvus.io/docs/overview.md

nsdb.io/Architecture

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Amazon

Community supported by Red Hat

Initial release

2016

2012

2014

2019

2017

Current release

2.3.4, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache Version 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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++, Go

Java, Scala

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

HTTP API

HTTP REST

RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

C
Java
Perl
Python
R

Go
Java
Python
Ruby

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

Java
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

automatic partitioning across Amazon Search Instance as required

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

managed transparently by AWS

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual 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

Using Apache Lucene

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

authentication via encrypted signatures

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Two Critical Flaws Found in Alibaba Cloud's PostgreSQL Databases
20 April 2023, The Hacker News

How Data Analytics Capabilities of Alibaba Group Evolve Its Ecosystem to the Cloud
20 February 2021, DataDrivenInvestor

provided by Google News

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Amazon CloudSearch – Even Better Searching for Less Than $100/Month | Amazon Web Services
24 March 2014, AWS Blog

Amazon Takes On Google And Microsoft With CloudSearch
16 April 2012, Forbes

AWS, Microsoft and Google should retire these cloud services
2 June 2020, TechTarget

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

provided by Google News

Share this page