Overview

IBM DB2

Stacks245

Followers254

Votes19

ScyllaDB

Stacks143

Followers197

Votes8

IBM DB2 vs Scylla: What are the differences?

## Introduction
This Markdown code provides a comparison between IBM DB2 and Scylla, highlighting key differences between the two.

1. **Data Model**: IBM DB2 follows a relational database model, organizing data into tables with predefined schemas. In contrast, Scylla uses a distributed and decentralized data model based on Apache Cassandra's architecture, which offers high availability and scalability for large-scale distributed systems.
  
2. **Consistency Model**: IBM DB2 ensures strong consistency by default, where all reads and writes are guaranteed to be linearizable. On the other hand, Scylla offers tunable consistency levels, allowing users to choose between strong or eventual consistency based on their application requirements and tradeoffs between performance and consistency.

3. **Performance**: IBM DB2 is optimized for OLTP (Online Transaction Processing) workloads, providing high performance for complex transactional queries. In comparison, Scylla is designed for high write throughput and low-latency querying, making it ideal for real-time analytics and fast data ingestion in high-volume applications.

4. **Deployment**: IBM DB2 is typically deployed as an on-premises solution or in private cloud environments, offering full control over the infrastructure and configurations. In contrast, Scylla is well-suited for cloud-native environments, supporting deployments on popular cloud platforms like AWS, Azure, and Google Cloud, as well as Kubernetes orchestration.

5. **Open Source Community**: Scylla is built on open-source technologies and actively contributes back to the community, providing users with access to a wide range of resources, tools, and community-driven support. In comparison, IBM DB2 is a commercial database management system with proprietary licensing and support, limiting the level of community involvement and customization options.

6. **Scalability**: Scylla is designed for linear scalability, enabling seamless horizontal scaling by adding more nodes to the cluster to handle increasing data volumes and user loads. While IBM DB2 also supports scalability through clustering and partitioning, the process may require more manual intervention and expertise compared to Scylla's automated and self-managing architecture.

In Summary, this Markdown code outlines key differences between IBM DB2 and Scylla, focusing on data model, consistency model, performance, deployment options, open-source community, and scalability aspects.

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Advice on IBM DB2, 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.

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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.

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Detailed Comparison

IBM DB2	ScyllaDB
DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs.	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 245	Stacks 143
Followers 254	Followers 197
Votes 19	Votes 8
Pros & Cons
Pros 7 Rock solid and very scalable 5 BLU Analytics is amazingly fast 2 Secure by default 2 Easy 2 Native XML support	Pros 2 Replication 1 Distributed 1 Fewer nodes 1 High performance 1 Written in C++
Integrations
Node.js JavaScript PHP Ruby Java Python C# .NET C++ Perl	KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark

What are some alternatives to IBM DB2, 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.