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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. HarperDB vs Scylla

HarperDB vs Scylla

OverviewDecisionsComparisonAlternatives

Overview

ScyllaDB
ScyllaDB
Stacks143
Followers197
Votes8
HarperDB
HarperDB
Stacks6
Followers18
Votes9

HarperDB vs Scylla: What are the differences?

<HarperDB and Scylla are both databases used for different applications, with HarperDB focusing on flexible data modeling and Scylla designed for high-throughput and low-latency requirements. Below are the key differences between HarperDB and Scylla.>

  1. Data Model: HarperDB offers a flexible data model that allows for schema-on-read and dynamic schema changes, making it suitable for applications with evolving data requirements. In contrast, Scylla follows a strictly defined schema-on-write approach, optimizing for high performance and predictable data storage structure.

  2. Consistency: HarperDB provides strong consistency guarantees with ACID transactions, ensuring data integrity across operations. On the other hand, Scylla offers eventual consistency by default, which enhances availability and performance but may lead to temporary data inconsistencies in certain scenarios.

  3. Scalability: HarperDB allows for horizontal scalability by distributing data across multiple nodes, enabling seamless scaling based on workload demands. Scylla, built on Apache Cassandra's architecture, also supports horizontal scaling for massive datasets while achieving low latency and high throughput.

  4. Query Language: HarperDB supports SQL-based queries, making it easier for developers familiar with relational databases to work with the platform. Scylla, being a NoSQL database, uses CQL (Cassandra Query Language) for interacting with the data store, offering a different querying paradigm optimized for distributed environments.

  5. Community Support: HarperDB has a growing community but may have a smaller user base compared to established database solutions. In contrast, Scylla benefits from the widespread adoption of Apache Cassandra, providing a larger community for support, resources, and third-party integrations.

  6. Use Cases: HarperDB is well-suited for applications that require flexible data modeling, real-time analytics, and rapid development cycles. Scylla is ideal for high-throughput, low-latency use cases such as real-time big data processing, IoT applications, and time-series data management.

In Summary, the key differences between HarperDB and Scylla lie in their data modeling approaches, consistency models, scalability options, query languages, community support, and target use cases.

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Advice on ScyllaDB, HarperDB

Tom
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
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

ScyllaDB
ScyllaDB
HarperDB
HarperDB

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.

Harper takes the "stack" out of "tech stack" by combining data storage, caching, application, and messaging functions into a single technology to achieve unmatched global low latency, simplicity, and cost performance at scale.

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
Cloud; Edge Computing; On Prem; Globally Distributed; Custom Functions; Database-as-a-service; Hybrid Cloud; Clustering and Replication; Fully-Indexed; Dynamic Schema; Small Footprint; SQL Query Engine; Full NoSQL Capabilities; Configurable Table-Level Pub/Sub; Built In API with Single End Point; Role Based Security; User Friendly Management Studio; Industry Standard Interfaces & Drivers;
Statistics
Stacks
143
Stacks
6
Followers
197
Followers
18
Votes
8
Votes
9
Pros & Cons
Pros
  • 2
    Replication
  • 1
    High performance
  • 1
    Written in C++
  • 1
    High availability
  • 1
    Scale up
Pros
  • 2
    Data api
  • 1
    Distribution capabilities
  • 1
    Cost efficient
  • 1
    Edge capabilities
  • 1
    Custom Functions
Integrations
KairosDB
KairosDB
Wireshark
Wireshark
JanusGraph
JanusGraph
Grafana
Grafana
Hackolade
Hackolade
Prometheus
Prometheus
Kubernetes
Kubernetes
Datadog
Datadog
Kafka
Kafka
Apache Spark
Apache Spark
Node.js
Node.js
GraphQL
GraphQL
Docker
Docker
.NET
.NET
Kubernetes
Kubernetes
Amazon S3
Amazon S3
React.js Boilerplate
React.js Boilerplate
uWebSockets
uWebSockets
Python
Python
Rust
Rust

What are some alternatives to ScyllaDB, HarperDB?

MongoDB

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

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

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

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

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

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

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

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

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

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.

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