DBMS > BoltDB vs. Heroic vs. Milvus vs. Teradata Aster vs. Tibero

System Properties Comparison BoltDB vs. Heroic vs. Milvus vs. Teradata Aster vs. Tibero

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

An embedded key-value store for Go.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Platform for big data analytics on multistructured data sources and types

A secure RDBMS, designed for easy portability from Oracle

Primary database model

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

github.com/boltdb/bolt

github.com/spotify/heroic

milvus.io

us.tmaxsoft.com/products/tibero

Technical documentation

spotify.github.io/heroic

milvus.io/docs/overview.md

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Spotify

Teradata

TmaxSoft

Initial release

2013

2014

2019

2005

2003

Current release

2.3.4, January 2024

6, April 2015

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

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

C and Assembler

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

C
C#
C++
Java
Python
R

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

R packages

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

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

planned for next version

User concepts

Access control

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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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More resources

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