DBMS > BigObject vs. Greenplum vs. LokiJS vs. Microsoft SQL Server vs. Milvus

System Properties Comparison BigObject vs. Greenplum vs. LokiJS vs. Microsoft SQL Server vs. Milvus

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Website

bigobject.io

greenplum.org

github.com/techfort/LokiJS

www.microsoft.com/en-us/sql-server

milvus.io

Technical documentation

docs.bigobject.io

docs.greenplum.org

techfort.github.io/LokiJS

learn.microsoft.com/en-US/sql/sql-server

milvus.io/docs/overview.md

Developer

BigObject, Inc.

Pivotal Software Inc.

Microsoft

Initial release

2015

2005

2014

1989

2019

Current release

7.0.0, September 2023

SQL Server 2022, November 2022

2.4.4, May 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

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.

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Zilliz Cloud – Cloud-native service for Milvus

Implementation language

JavaScript

C++

C++, Go

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

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

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

yes

schema-free

yes

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.

yes

since Version 4.2

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

Supported programming languages

C
Java
Perl
Python
R

JavaScript

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

Lua

yes

View functions in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

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

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