DBMS > Bangdb vs. Graph Engine vs. Hypertable vs. Milvus vs. STSdb

System Properties Comparison Bangdb vs. Graph Engine vs. Hypertable vs. Milvus vs. STSdb

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

Converged and high performance database for device data, events, time series, document and graph

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Graph DBMS
Time Series DBMS

Graph DBMS
Key-value store

Wide column store

Vector DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

bangdb.com

www.graphengine.io

milvus.io

github.com/STSSoft/STSdb4

Technical documentation

docs.bangdb.com

www.graphengine.io/docs/manual

milvus.io/docs/overview.md

Developer

Sachin Sinha, BangDB

Microsoft

Hypertable Inc.

STS Soft SC

Initial release

2012

2010

2009

2019

2011

Current release

BangDB 2.0, October 2021

0.9.8.11, March 2016

2.3.4, January 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT License

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

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, C++

.NET and C

C++

C++, Go

Server operating systems

Linux

.NET

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

Vector, Numeric and String

yes

primitive types and user defined types (classes)

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

secondary, composite, nested, reverse, geospatial

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

C++ API
Thrift

RESTful HTTP API

.NET Client API

Supported programming languages

C
C#
C++
Java
Python

C#
C++
F#
Visual Basic

C++
Java
Perl
PHP
Python
Ruby

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

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

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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