Overview

Vertica

Stacks88

Followers120

Votes16

ScyllaDB

Stacks143

Followers197

Votes8

Scylla vs Vertica: What are the differences?

## Key Differences between Scylla and Vertica

<Write Introduction here>

1. **Data Model**: Scylla uses a partitioned row store data model, while Vertica uses a column store data model. This means that Scylla stores data in rows and organizes them in partitions for faster retrieval, whereas Vertica stores data in columns which is more suitable for analytics and data warehousing.

2. **Consistency**: Scylla offers tunable consistency levels, allowing users to choose their desired balance between consistency and availability, while Vertica ensures strong consistency by default, making it ideal for applications where data accuracy is critical.

3. **Query Language**: Scylla uses CQL (Cassandra Query Language) which is similar to SQL with some specific differences such as lack of JOINs and subqueries, whereas Vertica supports SQL-based queries which are more user-friendly for traditional data analysts.

4. **Use Case**: Scylla is designed for real-time, high-throughput transactional workloads, making it suitable for applications like IoT, gaming, and ad-tech, while Vertica is tailored for analytics and data warehousing applications that require complex analytical queries and reporting.

5. **Distribution Model**: Scylla follows a masterless architecture where each node in the cluster has the same role, providing high availability and fault tolerance, while Vertica employs a shared-nothing distributed architecture with dedicated roles for different nodes, enabling parallel processing and scalability.

6. **Storage Management**: In Scylla, data is stored in SSTables (Sorted String Tables) with data partitioning and replication managed by the cluster, whereas Vertica utilizes a combination of row and columnar storage for optimized query performance and storage efficiency.

In Summary, Scylla and Vertica differ in their data models, consistency levels, query languages, use cases, distribution models, and storage management approaches, catering to different types of workload requirements.

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Advice on Vertica, 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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Comments

Detailed Comparison

Vertica	ScyllaDB
It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.	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.
Analyze All of Your Data. No longer move data or settle for siloed views;Achieve Scale and Performance;Fear of growing data volumes and users is a thing of the past;Future-Proof Your Analytics	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 88	Stacks 143
Followers 120	Followers 197
Votes 16	Votes 8
Pros & Cons
Pros 3 Shared nothing or shared everything architecture 1 Vertica is the only product which offers partition prun 1 Query-Optimized Storage 1 Fully automated Database Designer tool 1 Near-Real-Time Analytics in pure Column Store	Pros 2 Replication 1 High performance 1 Written in C++ 1 High availability 1 Scale up
Integrations
Oracle Golang MongoDB MySQL Sass Mode PowerBI Tableau Talend	KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark

What are some alternatives to Vertica, 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.