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  1. Stackups
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  5. Azure SQL Database vs Scylla

Azure SQL Database vs Scylla

OverviewDecisionsComparisonAlternatives

Overview

Azure SQL Database
Azure SQL Database
Stacks585
Followers502
Votes13
ScyllaDB
ScyllaDB
Stacks143
Followers197
Votes8

Azure SQL Database vs Scylla: What are the differences?

Introduction

Azure SQL Database and Scylla are both popular database management systems, but they have key differences that set them apart from each other. In this article, we will explore and highlight the main distinctions between these two systems.

  1. Scalability: Azure SQL Database is a fully managed relational database service while Scylla is a highly scalable NoSQL database. Azure SQL Database is designed to scale both vertically and horizontally by adjusting the compute resources and storage to meet the needs of the workload. On the other hand, Scylla is built to handle massive amounts of data with linear scalability, allowing it to handle millions of operations per second.

  2. Data Model: Azure SQL Database follows a structured data model based on tables with predefined schemas, supporting ACID (Atomicity, Consistency, Isolation, Durability) properties. Scylla, on the other hand, is a wide-column NoSQL database that employs a flexible schema and focuses on high write and read performance. It does not provide built-in support for ACID transactions.

  3. Consistency Strategy: Azure SQL Database offers strong consistency, ensuring that all replicas have the same data at the same time. It utilizes a distributed consensus protocol to maintain consistency. In contrast, Scylla offers tunable consistency, allowing users to configure the level of consistency they need. It employs eventual consistency by default, which means that updates may take some time to propagate across all replicas.

  4. Query Language: Azure SQL Database supports the widely used SQL (Structured Query Language), allowing users to perform complex queries using a declarative approach. Scylla, on the other hand, uses its own query language called CQL (Cassandra Query Language), which is similar to SQL but has some differences in syntax and functionality.

  5. Deployment Options: Azure SQL Database offers a flexible range of deployment options, including single databases, elastic pools, and managed instances. Users can choose the most suitable option depending on their needs and budget. Scylla, on the other hand, can be deployed on-premises or in the cloud, giving users the flexibility to run it in their preferred environment.

  6. Ecosystem Integration: Azure SQL Database is tightly integrated with other Azure services, such as Azure App Service and Azure Functions, making it easy to build and deploy applications. It also supports integration with other popular tools and frameworks like Entity Framework and Power BI. Scylla, on the other hand, has its own ecosystem with various integrations and plugins, including support for Apache Kafka and Apache Spark.

In summary, Azure SQL Database is a managed relational database service with strong consistency and a structured data model, while Scylla is a highly scalable NoSQL database with tunable consistency and a flexible schema. The choice between them depends on the specific requirements of the application and the desired trade-offs between scalability, consistency, and ease of integration.

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Advice on Azure SQL Database, ScyllaDB

Tom
Tom

CEO at Gentlent

Jun 9, 2020

Decided

The Gentlent Tech Team made lots of updates within the past year. The biggest one being our database:

We decided to migrate our #PostgreSQL -based database systems to a custom implementation of #Cassandra . This allows us to integrate our product data perfectly in a system that just makes sense. High availability and scalability are supported out of the box.

387k views387k
Comments
Vinay
Vinay

Head of Engineering

Sep 19, 2019

Needs advice

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

174k views174k
Comments

Detailed Comparison

Azure SQL Database
Azure SQL Database
ScyllaDB
ScyllaDB

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows.

-
High availability; horizontal scalability; vertical scalability; Cassandra compatible; DynamoDB compatible; wide column; NoSQL; lightweight transactions; change data capture; workload prioritization; shard-per-core; IO scheduler; self-tuning
Statistics
Stacks
585
Stacks
143
Followers
502
Followers
197
Votes
13
Votes
8
Pros & Cons
Pros
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable
Pros
  • 2
    Replication
  • 1
    Scale up
  • 1
    Distributed
  • 1
    Fewer nodes
  • 1
    High performance
Integrations
No integrations available
KairosDB
KairosDB
Wireshark
Wireshark
JanusGraph
JanusGraph
Grafana
Grafana
Hackolade
Hackolade
Prometheus
Prometheus
Kubernetes
Kubernetes
Datadog
Datadog
Kafka
Kafka
Apache Spark
Apache Spark

What are some alternatives to Azure SQL Database, ScyllaDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

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