DBMS > Microsoft Azure Synapse Analytics vs. Snowflake vs. Solr vs. Transwarp StellarDB

System Properties Comparison Microsoft Azure Synapse Analytics vs. Snowflake vs. Solr vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

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

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

A widely used distributed, scalable search engine based on Apache Lucene

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS

Search engine

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	44.28
Rank	#24	Overall
	#3	Search engines

Score	0.07
Rank	#361	Overall
	#38	Graph DBMS

Website

azure.microsoft.com/services/synapse-analytics

www.snowflake.com

solr.apache.org

www.transwarp.cn/en/product/stellardb

Technical documentation

docs.microsoft.com/azure/synapse-analytics

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

Developer

Microsoft

Snowflake Computing Inc.

Apache Software Foundation

Transwarp

Initial release

2016

2014

2006

Current release

9.5.0, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

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.

Implementation language

C++

Java

Server operating systems

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

OpenCypher

Supported programming languages

C#
Java
PHP

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Transact SQL

user defined functions

Java plugins

Triggers

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

yes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

yes

Transaction concepts

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

ACID

optimistic locking

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

User concepts

Access control

yes

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

yes

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