DBMS > Heroic vs. Milvus vs. SAP HANA vs. SingleStore

System Properties Comparison Heroic vs. Milvus vs. SAP HANA vs. SingleStore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

In-memory, column based data store. Available as appliance or cloud service

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Time Series DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

github.com/spotify/heroic

milvus.io

www.sap.com/products/hana.html

www.singlestore.com

Technical documentation

spotify.github.io/heroic

milvus.io/docs/overview.md

help.sap.com/hana

docs.singlestore.com

Developer

Spotify

SAP

SingleStore Inc.

Initial release

2014

2019

2010

2013

Current release

2.3.4, January 2024

2.0 SPS07 (April 4, 2023), April 2023

8.5, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

also available as a cloud based 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

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

C++, Go

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Appliance or cloud-service

Linux

64 bit version required

Data scheme

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

but no triggers and foreign keys

APIs and other access methods

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

RESTful HTTP API

JDBC
ODBC

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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 and fine grained access rights

yes

Fine grained access control via users, groups 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

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more

Competitive advantages

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

SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more

Typical application scenarios

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

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Customers in various industries worldwide including US and International Industry...
» more

Licensing and pricing models

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

F ree Tier and Enterprise Edition
» 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.