Overview

Event Store

Stacks69

Followers82

Votes1

ScyllaDB

Stacks143

Followers197

Votes8

Event Store vs Scylla: What are the differences?

Event Store and Scylla are two popular technologies used in the software industry for different purposes. In this analysis, we will outline the key differences between these two technologies.

Database Model: Event Store is a type of database that follows an event sourcing model, where events are stored as a log in an append-only fashion. On the other hand, Scylla is a NoSQL database that uses a column-family data model, similar to Apache Cassandra.
Data Consistency: Event Store provides strong consistency guarantees, ensuring that events are stored and processed in a specific order. It also supports optimistic concurrency control to handle concurrent writes. In contrast, Scylla offers eventual consistency, where data may temporarily diverge across replicas but eventually becomes consistent.
Scalability and Performance: Scylla is designed for high performance and scalability, capable of handling large volumes of data and high throughput. It is optimized to leverage the hardware resources efficiently, making it a suitable choice for applications with demanding performance requirements. Event Store, while also scalable, is more focused on providing strong consistency guarantees and is often used in event-driven architectures.
Query Capabilities: Scylla supports a wide range of queries using the Cassandra Query Language (CQL), including ad-hoc queries, range scans, and secondary indexes. It also provides support for aggregations and analytics through integration with Apache Spark. Event Store, on the other hand, is more specialized for event sourcing scenarios and provides specific query capabilities tailored for working with event streams.
Data Durability: Both Event Store and Scylla ensure data durability by persisting data to disk. However, Event Store also offers a feature called "at-least-once delivery," which guarantees that events will be stored even if errors or failures occur during processing. This ensures that events are not lost in case of failures.
Community and Ecosystem: Scylla benefits from its compatibility with the Apache Cassandra ecosystem. It can leverage existing tools, libraries, and community support, making it a popular choice for applications that require compatibility with Cassandra. Event Store, while also having an active community, has a smaller ecosystem and is more tailored for specific use cases.

In summary, Event Store is primarily intended for event sourcing scenarios, providing strong consistency guarantees, while Scylla focuses on scalability, performance, and compatibility with the Apache Cassandra ecosystem.

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Advice on Event Store, ScyllaDB

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

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

Event Store	ScyllaDB
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.	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.
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	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 69	Stacks 143
Followers 82	Followers 197
Votes 1	Votes 8
Pros & Cons
Pros 1 Trail Log	Pros 2 Replication 1 High performance 1 Written in C++ 1 High availability 1 Scale up
Integrations
.NET SQLite MySQL	KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark

What are some alternatives to Event Store, ScyllaDB?

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

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 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.

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 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

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 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

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 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

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.