Overview

ScyllaDB

Stacks143

Followers197

Votes8

MapD

Stacks32

Followers24

Votes4

MapD vs Scylla: What are the differences?

# Key Differences between MapD and Scylla

MapD and Scylla are two distinct database management systems with different use cases and functionalities.
1. **Database Type**: MapD is an in-memory SQL database that leverages GPUs for processing, making it ideal for complex analytics on large datasets. In contrast, Scylla is a NoSQL database designed for handling high-throughput, low-latency workloads, especially in distributed environments.
2. **Primary Use Case**: MapD is commonly used for data analytics and visualization tasks where speed and real-time insights are crucial. On the other hand, Scylla is preferred for applications requiring horizontal scaling and seamless data distribution across clusters.
3. **Consistency Model**: MapD follows a strict ACID-compliant consistency model, ensuring data integrity and reliability for transactional workflows. In contrast, Scylla offers tunable consistency levels to trade off between performance and data consistency based on use case requirements.
4. **Data Model**: MapD supports traditional relational data models with SQL queries, joins, and aggregations, making it familiar to SQL developers. Meanwhile, Scylla works with a wide-column store data model similar to Apache Cassandra, allowing for schema flexibility and wide distribution of data.
5. **Ecosystem Integration**: MapD typically integrates well with existing data analysis tools and frameworks like Jupyter, Tableau, and R for seamless data exploration and visualization. In comparison, Scylla integrates smoothly with popular NoSQL technologies like Kafka, Prometheus, and Grafana for monitoring and data pipelines.
6. **Deployment Complexity**: MapD requires specialized hardware with high-performance GPUs to leverage its full processing capabilities, potentially increasing the deployment cost. On the other hand, Scylla can run on standard hardware setups, offering more flexibility and cost-efficiency in deployment scenarios.

In Summary, MapD and Scylla differ in their database type, primary use cases, consistency models, data models, ecosystem integrations, and deployment complexities, catering to distinct needs in various database management scenarios.

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Advice on ScyllaDB, MapD

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

ScyllaDB	MapD
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.	Interactively query and visualize massive datasets with the parallel power of GPUs.
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	SQL; GPU-powered; column store; fast; scalable; interactive visualization; machine learning
Statistics
Stacks 143	Stacks 32
Followers 197	Followers 24
Votes 8	Votes 4
Pros & Cons
Pros 2 Replication 1 Written in C++ 1 High availability 1 Scale up 1 Distributed	Pros 3 Super fast, and the approach taken 1 Hehe
Integrations
KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark	Hadoop Amazon S3 Apache Spark Amazon Redshift MySQL Kafka PostgreSQL IBM DB2 Microsoft SQL Server Oracle

What are some alternatives to ScyllaDB, MapD?

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.