DBMS > Graph Engine vs. Graphite vs. Microsoft SQL Server vs. Milvus vs. QuestDB

System Properties Comparison Graph Engine vs. Graphite vs. Microsoft SQL Server vs. Milvus vs. QuestDB

Editorial information provided by DB-Engines

Name

Description

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Microsofts flagship relational DBMS

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

A high performance open source SQL database for time series data

Primary database model

Graph DBMS
Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

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

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Website

www.graphengine.io

github.com/graphite-project/graphite-web

www.microsoft.com/en-us/sql-server

milvus.io

questdb.io

Technical documentation

www.graphengine.io/docs/manual

graphite.readthedocs.io

learn.microsoft.com/en-US/sql/sql-server

milvus.io/docs/overview.md

questdb.io/docs

Developer

Microsoft

Chris Davis

Microsoft

QuestDB Technology Inc

Initial release

2010

2006

1989

2019

2014

Current release

SQL Server 2022, November 2022

2.3.4, January 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

Apache 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

.NET and C

Python

C++

C++, Go

Java (Zero-GC), C++, Rust

Server operating systems

.NET

Linux
Unix

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

Numeric data only

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL with time-series extensions

APIs and other access methods

RESTful HTTP API

HTTP API
Sockets

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

C#
C++
F#
Visual Basic

JavaScript (Node.js)
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, but depending on the SQL-Server Edition

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

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

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

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

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» 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

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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5 April 2024

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