DBMS > Geode vs. Microsoft SQL Server vs. Milvus vs. mSQL vs. PlanetScale

System Properties Comparison Geode vs. Microsoft SQL Server vs. Milvus vs. mSQL vs. PlanetScale

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Microsofts flagship relational DBMS

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Website

geode.apache.org

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

milvus.io

hughestech.com.au/products/msql

planetscale.com

Technical documentation

geode.apache.org/docs

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

milvus.io/docs/overview.md

planetscale.com/docs

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Microsoft

Hughes Technologies

PlanetScale

Initial release

2002

1989

2019

1994

2020

Current release

1.1, February 2017

SQL Server 2022, November 2022

2.3.4, January 2024

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

restricted free version is available

Open Source

Apache Version 2.0

commercial

free licenses can be provided

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++

C++, Go

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

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

RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

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

yes

proprietary syntax

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes, on a single node

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights per client and object definable

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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