DBMS > Drizzle vs. Hazelcast vs. Milvus vs. TempoIQ vs. Teradata Aster

System Properties Comparison Drizzle vs. Hazelcast vs. Milvus vs. TempoIQ vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A widely adopted in-memory data grid

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

hazelcast.com

milvus.io

tempoiq.com (offline)

Technical documentation

hazelcast.org/imdg/docs

milvus.io/docs/overview.md

Developer

Drizzle project, originally started by Brian Aker

Hazelcast

TempoIQ

Teradata

Initial release

2008

2019

2012

2005

Current release

7.2.4, September 2012

5.3.6, November 2023

2.3.4, January 2024

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses available

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

C++

Java

C++, Go

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

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

the object must implement a serialization strategy

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

RESTful HTTP API

HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C++
Java
PHP

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

C#
Java
JavaScript

Node.js
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

R packages

Triggers

hooks for callbacks inside the server can be used.

yes

Events

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Replicated Map

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

Role based access control and fine grained access rights

simple authentication-based access control

fine grained access rights according to SQL-standard

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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