DBMS > EXASOL vs. Milvus vs. Oracle vs. SwayDB vs. TDengine

System Properties Comparison EXASOL vs. Milvus vs. Oracle vs. SwayDB vs. TDengine

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Widely used RDBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Time Series DBMS and big data platform

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

www.exasol.com

milvus.io

www.oracle.com/database

swaydb.simer.au

github.com/taosdata/TDengine
tdengine.com

Technical documentation

www.exasol.com/resources

milvus.io/docs/overview.md

docs.oracle.com/en/database

docs.tdengine.com

Developer

Exasol

Oracle

Simer Plaha

TDEngine, previously Taos Data

Initial release

2000

2019

1980

2018

2019

Current release

2.3.4, January 2024

23c, September 2023

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GNU Affero GPL V3.0

Open Source

GPL V3, also commercial editions available

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

C++, Go

C and C++

Scala

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
Windows

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

Standard SQL with extensions for time-series applications

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
RESTful HTTP API

Supported programming languages

Java
Lua
Python
R

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Java
Kotlin
Scala

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

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

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

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

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

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

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

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» 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

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

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