DBMS > atoti vs. Axibase vs. CockroachDB vs. Milvus vs. RDF4J

System Properties Comparison atoti vs. Axibase vs. CockroachDB vs. Milvus vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

atoti.io

axibase.com/docs/atsd/finance

www.cockroachlabs.com

milvus.io

rdf4j.org

Technical documentation

docs.atoti.io

www.cockroachlabs.com/docs

milvus.io/docs/overview.md

rdf4j.org/documentation

Developer

ActiveViam

Axibase Corporation

Cockroach Labs

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2013

2015

2019

2004

Current release

15585

24.1.0, May 2024

2.3.4, January 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java

C++, Go

Java

Server operating systems

Linux

Linux
macOS
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Unix
Windows

Data scheme

yes

dynamic schema

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

yes, wire compatible with PostgreSQL

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

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

Java
PHP
Python

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication using RAFT

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

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

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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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