Overview

ArangoDB

Stacks273

Followers442

Votes192

ScyllaDB

Stacks143

Followers197

Votes8

ArangoDB vs Scylla: What are the differences?

Introduction: In this comparison, we will highlight key differences between ArangoDB and Scylla, two popular databases.

Data Model: ArangoDB utilizes a multi-model approach, supporting graphs, key-value pairs, and documents, allowing for greater flexibility in data modeling. On the other hand, Scylla focuses primarily on a wide-column store, emphasizing performance and scalability for big data applications.
Consistency: ArangoDB supports ACID transactions, offering strong consistency guarantees for data operations. In contrast, Scylla prioritizes high availability and partition tolerance, leading to eventual consistency with tunable consistency levels.
Query Language: ArangoDB uses AQL (ArangoDB Query Language), a SQL-like query language that supports complex queries across different data models. Scylla, being a wide-column store, interfaces with CQL (Cassandra Query Language), optimized for querying data in a distributed environment.
Scalability: Both databases are designed for scalability, but with different approaches. ArangoDB utilizes a distributed architecture for horizontal scalability, while Scylla leverages the shared-nothing architecture and consistent hashing to achieve high performance and linear scalability.
Performance: Scylla is known for its exceptional performance, achieving low latency and high throughput for read and write operations. ArangoDB also offers good performance, especially for graph data processing, although not as specialized as Scylla in certain use cases.
Community Support and Ecosystem: ArangoDB has a vibrant open-source community and ecosystem, offering various tools and integrations for developers. Scylla, being based on Apache Cassandra, benefits from a large community and ecosystem centered around Cassandra, providing extensive support and resources for users.

In Summary, the key differences between ArangoDB and Scylla lie in their data models, consistency models, query languages, scalability approaches, performance characteristics, and community support ecosystems.

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Advice on ArangoDB, 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

ArangoDB	ScyllaDB
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.	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.
multi-model nosql db; acid; transactions; javascript; database; nosql; sharding; replication; query language; joins; aql; documents; graphs; key-values; graphdb	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 273	Stacks 143
Followers 442	Followers 197
Votes 192	Votes 8
Pros & Cons
Pros 37 Grahps and documents in one DB 26 Intuitive and rich query language 25 Good documentation 25 Open source 21 Joins for collections Cons 3 Web ui has still room for improvement 2 No support for blueprints standard, using custom AQL	Pros 2 Replication 1 High performance 1 High availability 1 Scale up 1 Written in C++
Integrations
No integrations available	KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark

What are some alternatives to ArangoDB, 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.

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.