DBMS > AgensGraph vs. AlaSQL vs. LeanXcale vs. Milvus vs. XTDB

System Properties Comparison AgensGraph vs. AlaSQL vs. LeanXcale vs. Milvus vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

JavaScript DBMS library

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Graph DBMS
Relational DBMS

Document store
Relational DBMS

Key-value store
Relational DBMS

Vector DBMS

Document store

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

bitnine.net/agensgraph

alasql.org

www.leanxcale.com

milvus.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

bitnine.net/documentation

github.com/AlaSQL/alasql

milvus.io/docs/overview.md

www.xtdb.com/docs

Developer

Bitnine Global Inc.

Andrey Gershun & Mathias R. Wulff

LeanXcale

Juxt Ltd.

Initial release

2016

2014

2015

2019

Current release

2.1, December 2018

2.3.4, January 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

MIT-License

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

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

Clojure

Server operating systems

Linux
OS X
Windows

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

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

All OS with a Java 8 (and higher) VM
Linux

Data scheme

depending on used data model

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes, extensible-data-notation format

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

yes

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

yes

through Apache Derby

limited SQL, making use of Apache Calcite

APIs and other access methods

Cypher Query Language
JDBC

JavaScript API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

C
Java
JavaScript
Python

JavaScript

C
Java
Scala

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

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

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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