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  1. Stackups
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  4. Databases
  5. Event Store vs Microsoft SQL Server

Event Store vs Microsoft SQL Server

OverviewDecisionsComparisonAlternatives

Overview

Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
Event Store
Event Store
Stacks69
Followers82
Votes1

Event Store vs Microsoft SQL Server: What are the differences?

Introduction:

When considering data storage solutions for a website or application, it is essential to compare the features and capabilities of different databases. Event Store and Microsoft SQL Server are two popular choices, each offering distinct advantages and disadvantages. In this comparison, we will highlight the key differences between Event Store and Microsoft SQL Server.

  1. Data Modeling and Query Language: Event Store uses the Event Sourcing model which focuses on storing domain events as a log to reconstruct the current state of an entity. In contrast, Microsoft SQL Server employs a relational database model with structured query language (SQL) for querying and manipulating data. The choice between the two depends on the specific requirements of the application, with Event Store being more suitable for event-driven architectures.

  2. Scalability and Performance: Event Store is designed for high scalability and performance, particularly in scenarios where real-time data processing and event streaming are crucial. It can handle a large volume of concurrent write operations efficiently. On the other hand, Microsoft SQL Server offers robust scalability features but may require additional considerations and optimizations for intensive workload scenarios.

  3. Event Processing and Stream Support: Event Store excels in event processing and stream management, providing built-in functionalities for event sourcing, stream aggregation, and event replay. It is well-suited for handling complex event-driven architectures and processing streams of data in real-time. Microsoft SQL Server, while capable of storing and querying data effectively, may not offer the same level of built-in support for event-driven applications.

  4. Data Consistency and Transactions: Event Store supports transactional writes within a single stream or aggregate, ensuring data consistency at the stream level. In comparison, Microsoft SQL Server provides transactional support at the database level, allowing for ACID (Atomicity, Consistency, Isolation, Durability) properties across multiple tables and transactions. The choice between the two depends on the consistency requirements of the application.

  5. Deployment and Maintenance: Event Store is typically deployed as a standalone server or cluster, offering a lightweight and efficient solution for event sourcing and stream processing. Microsoft SQL Server, on the other hand, requires more extensive management and maintenance due to its relational database nature and potential dependencies on additional services. The decision on deployment options should consider the operational overhead and resource constraints of the project.

  6. Licensing and Cost: Event Store is available as an open-source solution with a community edition and a commercial version with additional features and support. In contrast, Microsoft SQL Server requires a licensing fee for commercial usage, with different editions offering varying levels of functionality and support. The choice between the two may be influenced by budget considerations and the specific features required for the project.

In Summary, Event Store and Microsoft SQL Server differ in their approach to data modeling, scalability, event processing, consistency, deployment, and licensing, catering to diverse needs in application development and data management.

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Advice on Microsoft SQL Server, Event Store

Erin
Erin

IT Specialist

Mar 10, 2020

Needs adviceonMicrosoft SQL ServerMicrosoft SQL ServerMySQLMySQLPostgreSQLPostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

  1. I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
668k views668k
Comments

Detailed Comparison

Microsoft SQL Server
Microsoft SQL Server
Event Store
Event Store

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

It stores your data as a series of immutable events over time, making it easy to build event-sourced applications. It can run as a cluster of nodes containing the same data, which remains available for writes provided at least half the nodes are alive and connected.

-
Guaranteed writes; High availability; Projections; Multiple client interfaces; Optimistic concurrency checks; Subscribe to streams with competing consumers; Great performance that scales; Multiple hosting options; Commercial support plans; Immutable data store; Atom subscriptions
Statistics
Stacks
21.3K
Stacks
69
Followers
15.5K
Followers
82
Votes
540
Votes
1
Pros & Cons
Pros
  • 139
    Reliable and easy to use
  • 101
    High performance
  • 95
    Great with .net
  • 65
    Works well with .net
  • 56
    Easy to maintain
Cons
  • 4
    Expensive Licensing
  • 2
    Microsoft
  • 1
    Replication can loose the data
  • 1
    Allwayon can loose data in asycronious mode
  • 1
    The maximum number of connections is only 14000 connect
Pros
  • 1
    Trail Log
Integrations
No integrations available
.NET
.NET
SQLite
SQLite
MySQL
MySQL

What are some alternatives to Microsoft SQL Server, Event Store?

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.

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.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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