DBMS > Apache Impala vs. Apache Kylin vs. Microsoft Azure Synapse Analytics vs. Neo4j vs. Snowflake

System Properties Comparison Apache Impala vs. Apache Kylin vs. Microsoft Azure Synapse Analytics vs. Neo4j vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	1.20
Rank	#175	Overall
	#80	Relational DBMS

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	44.47
Rank	#23	Overall
	#1	Graph DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

impala.apache.org

kylin.apache.org

azure.microsoft.com/services/synapse-analytics

neo4j.com

www.snowflake.com

Technical documentation

impala.apache.org/impala-docs.html

kylin.apache.org/docs

docs.microsoft.com/azure/synapse-analytics

neo4j.com/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation, originally contributed from eBay Inc

Microsoft

Neo4j, Inc.

Snowflake Computing Inc.

Initial release

2013

2015

2016

2007

2014

Current release

4.1.0, June 2022

3.1.0, July 2020

5.19, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

GPL version3, commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C++

Java

C++

Java, Scala

Server operating systems

Linux

hosted

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free and schema-optional

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
PHP

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Transact SQL

yes

User defined Procedures and Functions

user defined functions

Triggers

yes

via event handler

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

yes using Neo4j Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

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

yes

Relationships in graphs

yes

Transaction concepts

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

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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