DBMS > Hawkular Metrics vs. Lovefield vs. Milvus vs. SAP SQL Anywhere vs. Sequoiadb

System Properties Comparison Hawkular Metrics vs. Lovefield vs. Milvus vs. SAP SQL Anywhere vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.hawkular.org

google.github.io/lovefield

milvus.io

www.sap.com/products/technology-platform/sql-anywhere.html

www.sequoiadb.com

Technical documentation

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

github.com/google/lovefield/blob/master/docs/spec_index.md

milvus.io/docs/overview.md

help.sap.com/docs/SAP_SQL_Anywhere

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Community supported by Red Hat

Google

SAP

formerly Sybase

Sequoiadb Ltd.

Initial release

2014

2019

1992

2013

Current release

2.1.12, February 2017

2.3.4, January 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

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

JavaScript

C++, Go

C++

Server operating systems

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

via JavaScript builder pattern

yes

SQL-like query language

APIs and other access methods

HTTP REST

RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

Go
Java
Python
Ruby

JavaScript

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes, in C/C++, Java, .Net or Perl

JavaScript

Triggers

yes

via Hawkular Alerting

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Source-replica replication

Database mirroring

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

simple password-based access control

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.

Related products and services

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