DBMS > Blueflood vs. Graph Engine vs. Milvus vs. TempoIQ vs. TerarkDB

System Properties Comparison Blueflood vs. Graph Engine vs. Milvus vs. TempoIQ vs. TerarkDB

Editorial information provided by DB-Engines

Name

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

Description

Scalable TimeSeries DBMS based on Cassandra

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

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

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Vector DBMS

Time Series DBMS

Key-value store

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

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

Website

blueflood.io

www.graphengine.io

milvus.io

tempoiq.com (offline)

github.com/bytedance/terarkdb

Technical documentation

github.com/rax-maas/blueflood/wiki

www.graphengine.io/docs/manual

milvus.io/docs/overview.md

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Rackspace

Microsoft

TempoIQ

ByteDance, originally Terark

Initial release

2013

2010

2019

2012

2016

Current release

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache Version 2.0

commercial

restricted open source version available

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

Java

.NET and C

C++, Go

C++

Server operating systems

Linux
OS X

.NET

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

predefined scheme

yes

schema-free

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

SQL

Support of SQL

APIs and other access methods

HTTP REST

RESTful HTTP API

HTTP API

C++ API
Java API

Supported programming languages

C#
C++
F#
Visual Basic

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

C#
Java
JavaScript

Node.js
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

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

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

User concepts

Access control

Role based access control and fine grained access rights

simple authentication-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.

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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