DBMS > AlaSQL vs. Google Cloud Datastore vs. Milvus vs. Riak KV

System Properties Comparison AlaSQL vs. Google Cloud Datastore vs. Milvus vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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

Distributed, fault tolerant key-value store

Primary database model

Document store
Relational DBMS

Document store

Vector DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

alasql.org

cloud.google.com/datastore

milvus.io

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/datastore/docs

milvus.io/docs/overview.md

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Andrey Gershun & Mathias R. Wulff

Google

OpenSource, formerly Basho Technologies

Initial release

2014

2008

2019

2009

Current release

2.3.4, January 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2, commercial enterprise edition

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

JavaScript

C++, Go

Erlang

Server operating systems

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

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X

Data scheme

schema-free

Typing

predefined data types such as float or date

yes, details here

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

restricted

SQL

Support of SQL

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

SQL-like query language (GQL)

APIs and other access methods

JavaScript API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

JavaScript

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

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

using Google App Engine

Erlang

Triggers

yes

Callbacks using the Google Apps Engine

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using Paxos

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

links between data sets can be stored

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Concurrency

Support for concurrent manipulation of data

yes

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role based access control and fine grained access rights

yes, using Riak Security

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.

Related products and services

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