DBMS > Cachelot.io vs. EJDB vs. Faircom EDGE vs. Hypertable vs. Milvus

System Properties Comparison Cachelot.io vs. EJDB vs. Faircom EDGE vs. Hypertable vs. Milvus

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

In-memory caching system

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Primary database model

Key-value store

Document store

Key-value store
Relational DBMS

Wide column store

Vector DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

cachelot.io

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-edge

milvus.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

milvus.io/docs/overview.md

Developer

Softmotions

FairCom Corporation

Hypertable Inc.

Initial release

2015

2012

1979

2009

2019

Current release

V3, October 2020

0.9.8.11, March 2016

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

GPLv2

commercial

Restricted, free version available

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

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++

ANSI C, C++

C++

C++, Go

Server operating systems

FreeBSD
Linux
OS X

server-less

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI Standard SQL Types

Vector, Numeric and 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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

ANSI SQL queries

APIs and other access methods

Memcached protocol

in-process shared library

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

C++ API
Thrift

RESTful HTTP API

Supported programming languages

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

when using SQL

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

across SQL and NoSQL

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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

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

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