DBMS > Cachelot.io vs. Heroic vs. LevelDB vs. Milvus vs. SAP Advantage Database Server

System Properties Comparison Cachelot.io vs. Heroic vs. LevelDB vs. Milvus vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

In-memory caching system

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

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

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Website

cachelot.io

github.com/spotify/heroic

github.com/google/leveldb

milvus.io

www.sap.com/products/advantage-database-server.html

Technical documentation

spotify.github.io/heroic

github.com/google/leveldb/blob/main/doc/index.md

milvus.io/docs/overview.md

Developer

Spotify

Google

Sybase, SAP

Initial release

2015

2014

2011

2019

1993

Current release

1.23, February 2021

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache 2.0

Open Source

BSD

Open Source

Apache Version 2.0

commercial

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

C++

Java

C++

C++, Go

Server operating systems

FreeBSD
Linux
OS X

Illumos
Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

Memcached protocol

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

Role based access control and fine grained access rights

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

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.

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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