HBase vs MariaDB

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HBase

453
492
+ 1
15
MariaDB

16K
12.4K
+ 1
468
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HBase vs MariaDB: What are the differences?

What is HBase? The Hadoop database, a distributed, scalable, big data store. 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.

What is MariaDB? An enhanced, drop-in replacement for MySQL. 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.

HBase and MariaDB can be primarily classified as "Databases" tools.

"Performance" is the primary reason why developers consider HBase over the competitors, whereas "Drop-in mysql replacement" was stated as the key factor in picking MariaDB.

HBase and MariaDB are both open source tools. It seems that HBase with 2.91K GitHub stars and 2.01K forks on GitHub has more adoption than MariaDB with 2.82K GitHub stars and 864 GitHub forks.

Grooveshark, Shutterstock, and Geocodio are some of the popular companies that use MariaDB, whereas HBase is used by Pinterest, HubSpot, and Yammer. MariaDB has a broader approval, being mentioned in 496 company stacks & 461 developers stacks; compared to HBase, which is listed in 54 company stacks and 18 developer stacks.

Advice on HBase and MariaDB
Needs advice
on
HBaseHBaseMilvusMilvus
and
RocksDBRocksDB

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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Replies (1)
Emily Kurze
Recommends

You've probably come to a decision already but for those reading...here are some resources we put together to help people learn more about Milvus and other databases https://zilliz.com/comparison and https://github.com/zilliztech/VectorDBBench. I don't think they include RocksDB or HBase yet (you could could recommend on GitHub) but hopefully they help answer your Elastic Search questions.

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Maxim Ryakhovskiy
Needs advice
on
MariaDBMariaDBMongooseMongoose
and
PostgreSQLPostgreSQL

Hi all. I am an informatics student, and I need to realise a simple website for my friend. I am planning to realise the website using Node.js and Mongoose, since I have already done a project using these technologies. I also know SQL, and I have used PostgreSQL and MySQL previously.

The website will show a possible travel destination and local transportation. The database is used to store information about traveling, so only admin will manage the content (especially photos). While clients will see the content uploaded by the admin. I am planning to use Mongoose because it is very simple and efficient for this project. Please give me your opinion about this choice.

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Replies (7)

The use case you are describing would benefit from a self-hosted headless CMS like contentful. You can also go for Strapi with a database of your choice but here you would have to host Strapi and the underlying database (if not using SQLite) yourself. If you want to use Strapi, you can ease your work by using something like PlanetSCaleDB as the backing database for Strapi.

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Reza Malek
at Meam Software Engineering Group · | 4 upvotes · 216.3K views
Recommends
on
MongooseMongoosePostgreSQLPostgreSQL

Your requirements seem nothing special. on the other hand, MongoDB is commonly used with Node. you could use Mongo without defining a Schema, does it give you any benefits? Also, note that development speed matters. In most cases RDBMS are the best choice, Learn and use Postgres for life!

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Tarun Batra
Senior Software Developer at Okta · | 2 upvotes · 208.6K views
Recommends
on
MongooseMongoose

MongoDB and Mongoose are commonly used with Node.js and the use case doesn't seem to be requiring any special considerations as of now. However using MongoDB now will allow you to easily expand and modify your use case in future.

If not MongoDB, then my second choice will be PostgreSQL. It's a generic purpose database with jsonb support (if you need it) and lots of resources online. Nobody was fired for choosing PostgreSQL.

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Nutchanon Ninyawee

SQL is not so good at query lat long out of the box. you might need to use additional tools for that like UTM coordinates or Uber's H3.

If you use mongoDB, it support 2d coordinate query out of the box.

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Recommends
on
MongooseMongoose

Any database will be a great choice for your app, which is less of a technical challenge and more about great content. Go for it, the geographical search features maybe be actually handy for you.

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Ruslan Rayanov
Recommends

Hi, Maxim! Most likely, the site is almost ready. But we would like to share our development with you. https://falcon.web-automation.ru/ This is a constructor for web application. With it, you can create almost any site with different roles which have different levels of access to information and different functionality. The platform is managed via sql. knowing sql, you will be able to change the business logic as necessary and during further project maintenance. We will be glad to hear your feedback about the platform.

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Václav Hodek
CEO, lead developer at Localazy · | 1 upvotes · 209K views
Recommends
on
PostgreSQLPostgreSQL

Any database engine should work well but I vote for Postgres because of PostGIS extension that may be handy for travel related site. There's nothing special about your requirements.

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Decisions about HBase and MariaDB
Omran Jamal
CTO & Co-founder at Bonton Connect · | 4 upvotes · 523.3K views

We actually use both Mongo and SQL databases in production. Mongo excels in both speed and developer friendliness when it comes to geospatial data and queries on the geospatial data, but we also like ACID compliance hence most of our other data (except on-site logs) are stored in a SQL Database (MariaDB for now)

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Pros of HBase
Pros of MariaDB
  • 9
    Performance
  • 5
    OLTP
  • 1
    Fast Point Queries
  • 149
    Drop-in mysql replacement
  • 100
    Great performance
  • 74
    Open source
  • 55
    Free
  • 44
    Easy setup
  • 15
    Easy and fast
  • 14
    Lead developer is "monty" widenius the founder of mysql
  • 6
    Also an aws rds service
  • 4
    Consistent and robust
  • 4
    Learning curve easy
  • 2
    Native JSON Support / Dynamic Columns
  • 1
    Real Multi Threaded queries on a table/db

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What is HBase?

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.

What is 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.

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What companies use HBase?
What companies use MariaDB?
See which teams inside your own company are using HBase or MariaDB.
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Jun 24 2020 at 4:42PM

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Amazon S3KafkaHBase+4
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2004
What are some alternatives to HBase and MariaDB?
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.
Google Cloud Bigtable
Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.
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.
Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
See all alternatives