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

HarperDB vs Memcached

OverviewComparisonAlternatives

Overview

Memcached
Memcached
Stacks7.9K
Followers5.7K
Votes473
GitHub Stars14.0K
Forks3.3K
HarperDB
HarperDB
Stacks6
Followers18
Votes9

HarperDB vs Memcached: What are the differences?

Introduction

HarperDB and Memcached are two distinct technologies, each with its own unique set of features and capabilities. Understanding the key differences between HarperDB and Memcached can help in making an informed decision on which technology to use for a specific use case.

  1. Data Storage: HarperDB is a fully indexed, SQL-based database that can store and query structured data using traditional SQL queries. On the other hand, Memcached is an in-memory key-value store that is used for caching data to improve performance.

  2. Persistence: HarperDB provides persistent storage by default, ensuring data durability even in the case of unexpected shutdowns or failures. In contrast, Memcached does not inherently provide data persistence and relies on external solutions for data durability.

  3. Data Structure: While HarperDB supports complex data structures, relationships, and indexing, Memcached is best suited for simple key-value pairs and lacks support for complex data structures and relationships.

  4. Query Language: HarperDB supports SQL queries, allowing for complex data retrieval and manipulation through standard SQL syntax. On the other hand, Memcached does not support complex querying capabilities and is primarily used for quickly fetching cached data based on keys.

  5. Scalability: HarperDB offers built-in horizontal scaling capabilities, allowing for seamless distribution of data across multiple nodes for improved performance and availability. Memcached, on the other hand, may require additional configurations and third-party solutions for achieving scalability in distributed environments.

  6. Use Cases: HarperDB is well-suited for applications that require structured data storage, complex querying, and durability guarantees. Memcached, on the other hand, is ideal for applications where fast data access and caching are crucial for improving performance.

In Summary, HarperDB and Memcached differ in their approach to data storage, persistence, data structure, query language, scalability, and use cases.

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Detailed Comparison

Memcached
Memcached
HarperDB
HarperDB

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.

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.

-
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
GitHub Stars
14.0K
GitHub Stars
-
GitHub Forks
3.3K
GitHub Forks
-
Stacks
7.9K
Stacks
6
Followers
5.7K
Followers
18
Votes
473
Votes
9
Pros & Cons
Pros
  • 139
    Fast object cache
  • 129
    High-performance
  • 91
    Stable
  • 65
    Mature
  • 33
    Distributed caching system
Cons
  • 2
    Only caches simple types
Pros
  • 2
    Data api
  • 1
    Integration
  • 1
    Edge capabilities
  • 1
    Flexibility
  • 1
    Cost efficient
Integrations
No integrations available
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 Memcached, 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.

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.

InfluxDB

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.

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