DBMS > AlaSQL vs. Dgraph vs. GridGain vs. Milvus vs. MySQL

System Properties Comparison AlaSQL vs. Dgraph vs. GridGain vs. Milvus vs. MySQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Distributed and scalable native Graph DBMS

GridGain is an in-memory computing platform, built on Apache Ignite

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

Widely used open source RDBMS

Primary database model

Document store
Relational DBMS

Graph DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

dgraph.io/docs

www.gridgain.com/docs/index.html

milvus.io/docs/overview.md

dev.mysql.com/doc

Developer

Andrey Gershun & Mathias R. Wulff

Dgraph Labs, Inc.

GridGain Systems, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

2016

2007

2019

1995

Current release

GridGain 8.5.1

2.4.4, May 2024

9.0.0, July 2024

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache 2.0

commercial, open source

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are 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

JavaScript

Java, C++, .Net, Python, REST, SQL

C++, Go

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Linux
OS X
Solaris
Windows
z/OS

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
OS X
Solaris
Windows

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

ANSI-99 for query and DML statements, subset of DDL

yes

with proprietary extensions

APIs and other access methods

JavaScript API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

JavaScript

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

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

yes (compute grid and cache interceptors can be used instead)

yes

proprietary syntax

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication via Raft

yes (replicated cache)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

not for MyISAM storage engine

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Planned for future releases

Role-based access control
Security Hooks for custom implementations

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

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Competitive advantages

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Typical application scenarios

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Key customers

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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

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