DBMS > Microsoft SQL Server vs. Milvus vs. OpenSearch vs. Tarantool

System Properties Comparison Microsoft SQL Server vs. Milvus vs. OpenSearch vs. Tarantool

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Vector DBMS

Search engine

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Vector DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

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

milvus.io

github.com/opensearch-project
opensearch.org

www.tarantool.io

Technical documentation

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

milvus.io/docs/overview.md

opensearch.org/docs/latest

www.tarantool.io/en/doc

Developer

Microsoft

Amazon Web Services

Initial release

1989

2019

2021

2008

Current release

SQL Server 2022, November 2022

2.3.4, January 2024

2.5.0, January 2023

2.10.0, May 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.

Implementation language

C++

C++, Go

Java

C and C++

Server operating systems

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

All OS with a Java VM

BSD
Linux
macOS

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

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

RESTful HTTP API

Java API
RESTful HTTP/JSON API

Open binary protocol

Supported programming languages

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

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

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

yes

Lua, C and SQL stored procedures

Triggers

yes

by using the 'percolation' feature

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» 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

The OpenSearch Project offers open source software licensed under Apache License...
» 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.