DBMS > AlaSQL vs. Apache Drill vs. Machbase Neo vs. Milvus vs. RavenDB

System Properties Comparison AlaSQL vs. Apache Drill vs. Machbase Neo vs. Milvus vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

TimeSeries DBMS for AIoT and BigData

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store
Relational DBMS

Time Series DBMS

Vector DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

Technical documentation

github.com/AlaSQL/alasql

drill.apache.org/docs

machbase.com/dbms

milvus.io/docs/overview.md

ravendb.net/docs

Developer

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation

Machbase

Hibernating Rhinos

Initial release

2014

2012

2013

2019

2010

Current release

1.20.3, January 2023

V8.0, August 2023

2.4.4, May 2024

5.4, July 2022

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2

commercial

free test version available

Open Source

Apache Version 2.0

Open Source

AGPL version 3, 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

JavaScript

C++, Go

Server operating systems

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

Linux
OS X
Windows

Linux
macOS
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

SQL

Support of SQL

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

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

SQL-like query language (RQL)

APIs and other access methods

JavaScript API

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

JavaScript

C++

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

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

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

Depending on the underlying data source

yes

In-memory capabilities

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

yes

Depending on the underlying data source

yes

volatile and lookup table

yes

User concepts

Access control

Depending on the underlying data source

simple password-based access control

Role based access control and fine grained access rights

Authorization levels configured per client per database

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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