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HBase

374
462
+ 1
15
MemSQL

80
168
+ 1
32
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HBase vs MemSQL: What are the differences?

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; MemSQL: Database for real-time transactions and analytics. MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

HBase can be classified as a tool in the "Databases" category, while MemSQL is grouped under "In-Memory Databases".

HBase is an open source tool with 2.91K GitHub stars and 2.01K GitHub forks. Here's a link to HBase's open source repository on GitHub.

Pinterest, HubSpot, and hike are some of the popular companies that use HBase, whereas MemSQL is used by Shutterstock, Zynga, and StreetHawk. HBase has a broader approval, being mentioned in 54 company stacks & 18 developers stacks; compared to MemSQL, which is listed in 10 company stacks and 4 developer stacks.

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Pros of HBase
Pros of MemSQL
  • 9
    Performance
  • 5
    OLTP
  • 1
    Fast Point Queries
  • 8
    Distributed
  • 4
    Realtime
  • 3
    Columnstore
  • 3
    Sql
  • 3
    Concurrent
  • 3
    JSON
  • 2
    Ultra fast
  • 2
    Scalable
  • 1
    Availability Group
  • 1
    Pipeline
  • 1
    Mixed workload
  • 1
    Unlimited Storage Database

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- No public GitHub repository available -

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 MemSQL?

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

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Jobs that mention HBase and MemSQL as a desired skillset
What companies use HBase?
What companies use MemSQL?
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What tools integrate with MemSQL?

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Blog Posts

Jun 24 2020 at 4:42PM

Pinterest

Amazon S3KafkaHBase+4
4
1129
MySQLKafkaApache Spark+6
2
1809
What are some alternatives to HBase and MemSQL?
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