Featured Products: Datastax Astra RaimaDB SingleStore Milvus Neo4j

DBMS > Apache Impala vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Milvus vs. SQL.JS

System Properties Comparison Apache Impala vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Milvus vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Relational DBMS

Secondary database models

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

impala.apache.org

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

Technical documentation

impala.apache.org/impala-docs.html

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

milvus.io/docs/overview.md

sql.js.org/documentation/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Spotify

Microsoft

Alon Zakai

enhancements implemented by others

Initial release

2013

2014

2016

2019

2012

Current release

4.1.0, June 2022

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Cloud-based only

Only available as a cloud service

no

no

yes

no

no

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++

Java

C++

C++, Go

JavaScript

Server operating systems

Linux

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

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

Data scheme

yes

schema-free

yes

yes

Typing

predefined data types such as float or date

yes

yes

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.

no

no

no

no

no

Secondary indexes

yes

yes

via Elasticsearch

yes

no

SQL

Support of SQL

SQL-like DML and DDL statements

no

yes

no

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
ODBC

RESTful HTTP API

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
PHP

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

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

no

Transact SQL

no

no

Triggers

no

no

no

no

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

no

no

no

no

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

none

Foreign keys

Referential integrity

no

no

no

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

no

yes

Transaction concepts

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

no

no

ACID

no

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

yes

Durability

Support for making data persistent

yes

yes

yes

yes

no

except by serializing a db to a file

In-memory capabilities

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

no

no

yes

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

Role based access control and fine grained access rights

no

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

StarRocks Brings Speedy OLAP Database to the Cloud
14 July 2022, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT | Amazon Web Services
18 October 2023, AWS Blog

Azure Synapse Runtime for Apache Spark 3.2 End of Support | Azure updates
22 March 2024, Microsoft

Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

Azure Synapse Analytics: Everything you need to know about Microsoft's cloud analytics platform
24 September 2023, DataScientest

Azure Synapse Link for Cosmos DB: New Analytics Capabilities
10 November 2023, InfoQ.com

provided by Google News

What Is Milvus Vector Database?
6 October 2023, The New Stack

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

provided by Google News

9 Best JavaScript and TypeScript ORMs for 2024 — SitePoint
22 March 2023, SitePoint

Execute millions of SQL statements in milliseconds in the browser with WebAssembly and Web Workers.
14 January 2017, hackernoon.com

SQLite On The Web: Absurd-sql
24 August 2021, Hackaday

In Praise Of SQLite
28 July 2022, iProgrammer

Running PostgreSQL Inside Your Browser
8 September 2022, iProgrammer

provided by Google News

Share this page

Featured Products

Present your product here