HBase vs Memcached

Overview

Memcached

Stacks7.9K

Followers5.7K

Votes473

GitHub Stars14.0K

Forks3.3K

HBase

Stacks511

Followers498

Votes15

GitHub Stars5.5K

Forks3.4K

HBase vs Memcached: What are the differences?

Introduction: HBase and Memcached are both popular data storage solutions used in modern web applications. However, they serve different purposes and have distinct features that make them suitable for specific use cases.

Data Model: HBase is a distributed, column-oriented database that stores data in a tabular format with rows and columns, similar to a traditional RDBMS. On the other hand, Memcached is an in-memory key-value store that caches data in memory for fast retrieval.
Consistency: HBase offers strong consistency guarantees, ensuring that data is always up-to-date and correct. In contrast, Memcached sacrifices consistency for performance by allowing eventual consistency, which means data may not always be immediately consistent across all nodes in a distributed system.
Persistence: HBase stores data persistently on disk, providing durability and fault-tolerance in case of node failures. Memcached, being an in-memory store, does not have built-in persistence mechanisms and relies on external solutions for data durability.
Scalability: HBase is designed for horizontal scalability, allowing users to add more nodes to handle increasing data volumes and traffic. Memcached, while also horizontally scalable, may require additional capacity planning to ensure performance as the dataset grows.
Query Language: HBase supports querying data using Apache Hadoop's ecosystem tools like Apache Hive and Apache Pig, making it suitable for complex analytical queries. In contrast, Memcached does not have built-in query capabilities and is primarily used for simple key-value lookups.
Use Cases: HBase is commonly used for applications requiring real-time data processing, analytics, and strong consistency guarantees. Memcached, on the other hand, is often employed for caching frequently accessed data or temporary storage to improve application performance.

In Summary, HBase and Memcached differ in terms of data model, consistency, persistence, scalability, query language support, and use cases.

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Advice on Memcached, HBase

Feb 9, 2022

Needs adviceon

Milvus

HBase

RocksDB

I am researching different querying solutions to handle ~1 trillion records of data (in the realm of a petabyte). The data is mostly textual. I have identified a few options: Milvus, HBase, RocksDB, and Elasticsearch. I was wondering if there is a good way to compare the performance of these options (or if anyone has already done something like this). I want to be able to compare the speed of ingesting and querying textual data from these tools. Does anyone have information on this or know where I can find some? Thanks in advance!

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Detailed Comparison

Memcached	HBase
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.	Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
Statistics
GitHub Stars 14.0K	GitHub Stars 5.5K
GitHub Forks 3.3K	GitHub Forks 3.4K
Stacks 7.9K	Stacks 511
Followers 5.7K	Followers 498
Votes 473	Votes 15
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 9 Performance 5 OLTP 1 Fast Point Queries

What are some alternatives to Memcached, HBase?

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.

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.

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.

Related Comparisons

HBase vs Memcached: What are the differences?

Data Model: HBase is a distributed, column-oriented database that stores data in a tabular format with rows and columns, similar to a traditional RDBMS. On the other hand, Memcached is an in-memory key-value store that caches data in memory for fast retrieval.
Consistency: HBase offers strong consistency guarantees, ensuring that data is always up-to-date and correct. In contrast, Memcached sacrifices consistency for performance by allowing eventual consistency, which means data may not always be immediately consistent across all nodes in a distributed system.
Persistence: HBase stores data persistently on disk, providing durability and fault-tolerance in case of node failures. Memcached, being an in-memory store, does not have built-in persistence mechanisms and relies on external solutions for data durability.
Scalability: HBase is designed for horizontal scalability, allowing users to add more nodes to handle increasing data volumes and traffic. Memcached, while also horizontally scalable, may require additional capacity planning to ensure performance as the dataset grows.
Query Language: HBase supports querying data using Apache Hadoop's ecosystem tools like Apache Hive and Apache Pig, making it suitable for complex analytical queries. In contrast, Memcached does not have built-in query capabilities and is primarily used for simple key-value lookups.
Use Cases: HBase is commonly used for applications requiring real-time data processing, analytics, and strong consistency guarantees. Memcached, on the other hand, is often employed for caching frequently accessed data or temporary storage to improve application performance.

In Summary, HBase and Memcached differ in terms of data model, consistency, persistence, scalability, query language support, and use cases.

HBase vs Memcached

Overview