HBase vs Cassandra: Which is The Best NoSQL Database for 2022?

  1. What is NoSQL Database?
  2. HBase Overview
  3. Cassandra Overview
  4. HBase vs Cassandra: Similarities
  5. HBase vs Cassandra: Comparision
  6. HBase vs Cassandra: When to use what?

What is a NoSQL database?

Why pick Open- Source NoSQL Database?

Here are some reasons to pick an Open source NoSQL Database for project development.

  1. Capable of handling a vast volume of data, regardless of the data type, that is highly scalable.
  2. It is highly scalable and can handle massive amounts of data.
  3. It has a lot of memory and a powerful CPU.
  4. There are no hard and fast rules for cache-dependent read and write operations.
  5. There will be no database errors.
  6. There is no RDBMS model among the NoSQL choices.

HBase Overview

Apache HBase is a distributed open-source, reliable wide column store database based on Google’s Bigtable. It was created as part of Apache’s Hadoop project in 2008. The Hadoop Distributed File System is used to run it (HDBS). Instead of MapReduce jobs, its activities run in real-time on its database. The in-memory operation, compression, and Bloom filters are among the characteristics it draws from Bigtable. HBase is a Java-based database that supports external APIs such as Thrift, Avro, Scala, Jython, and REST. Hbase has a stand-alone version of its database, but it’s primarily used for development purposes rather than for production.

Advantages:

The following are some of the key features and benefits of the Hbase database:

  • It uses a document-oriented database, with data saved as keys or values.
  • Hbase is well-suited for range-based scanning and offers smooth scaling.
  • Hbase includes Bigtable, Bloom filters, and block caches, all of which aid in query optimization.
  • Tables are included in Hbase, although a schema is only required for tables, not columns.
  • Hbase is written in a proprietary language that must be mastered to conduct queries.

Drawbacks:

  • There is no transaction support available here.
  • Hbase uses a traditional master-slave architecture, which takes a long time to fail from one HMaster to the next. Single-point failure occurs as a result of this.
  • JOINS are handled in the MapReduce layer here.

Key customers:

Netflix, 23andMe, Salesforce, Bloomberg, Xiaomi, Yahoo, Sophos, Adobe.

Cassandra Overview

Apache Cassandra is the most widely used wide column store database system, which was first open-sourced in 2008 and then designated a top-level Apache project on February 17, 2010.

Advantages:

The following are some of the key features and benefits of the Cassandra database:

  • Apache uses column storage with a large number of columns.
  • Cassandra has high availability and no single point of failure.
  • Cassandra is capable of quick reads and writes.
  • Apache Cassandra does not require any secondary indexes.
  • It provides excellent write and read throughput.

Drawbacks:

  • There is no sufficient support for ACID characteristics in this environment.
  • Aggregates are not supported by Cassandra.
  • Replicas may become inconsistent when the architecture is dispersed.
  • When the primary key is unknown, the scanning day suffers.

Key customers:

Netflix, Reddit, eBay, McDonald’s, Facebook, Walmart, GitHub, Comcast, Instagram, CERN

HBase vs Cassandra: Similarities Factors

There are a few similarities between HBase and Cassandra. Let’s check those out:

1. Database

HBase and Cassandra are both open-source NoSQL databases. Cassandra and HBase were created with Big Data. Both databases can handle non-relational data and handle exceedingly massive data collections as well as non-relational data such as photos, audio, and videos.

2. Replication

There is a safeguard in place for both HBase and Cassandra that avoids data loss even if the system fails. This is accomplished by using the replication mode. The data written on one node is replicated across the cluster’s multiple nodes. If a node fails, a backup node is always available to access data.

3. Scalability

High linear scalability is a property of both Cassandra and HBase. To handle more data, the user just needs to expand the cluster’s number of nodes. They are both excellent choices for processing massive amounts of data because of this feature.

4. Coding/ Programming

Both may be accessible primarily using Java, which is also the language in which they were created. Both databases are column-oriented and follow the same write routes. In a database, columns are the primary storage unit. Columns can be added by users based on their needs. Furthermore, the correct approach begins with a write operation being logged to a log file. It is mostly done to ensure long-term stability.

HBase vs Cassandra: Comparision Factors

Let’s compare HBase vs Cassandra and decide which one is the best NoSQL database.

1. Data Model

One of Cassandra’s important features is that it only permits a primary key to have multiple columns, whereas HBase only provides one column row keys and leaves the row key design to the developers. Cassandra’s primary key also includes the partition key and the clustering columns, with the partition key containing many columns.

2. Architecture

3. Infrastructure

Hadoop Infrastructure is used by HBase. Several moving pieces make up the HBase-Hadoop system, including Zookeeper, HBase master, Data nodes, and Name Node.

4. Performance

5. Support

When we compare HBase vs Cassandra, HBase does not allow ordered partitioning, whereas Cassandra does. Ordered partitioning reduces Cassandra’s row size to tens of gigabytes. HBase can use a coprocessor. While Cassandra supports many things, she does not support a few. Cassandra also has limitations when it comes to range-based row searches. Cassandra also does not provide coprocessor-like capabilities.

6. Security

HBase and Cassandra both provide database-wide access control as well as granularity to a certain extent. But, when we differentiate between HBase vs Cassandra, Cassandra supports access at the row level, whereas HBase goes one step further and permits access at the cell level. Cassandra assigns responsibilities and conditions to users, but HBase works in the opposite direction, with administrators assigning visibility labels to data sets and then informing user groups which label they may access.

7. Internode Communication

Internode communication is available in both HBase and Cassandra. While Cassandra employs the Gossip Protocol, HBase employs the Zookeeper Protocol, in which a single node serves as the master and the other nodes receive the required data.

8. Transactions

In terms of transactions comparison between HBase vs Cassandra, HBase primarily employs two types of mechanisms: Check and Put and Read Check Delete. Cassandra has a lightweight transaction capability built-in. We can see a variety of methods here, including Row-Level Write Isolation and Compare and Set.

9. Documentation

When it comes to documentation comparison between HBase vs Cassandra, the documentation for Cassandra is far superior to that of HBase. Working with and learning Cassandra gets easier as a result of this.

10. Query Language

While comparing HBase vs Cassandra, although the JRuby shell is used by both HBase and Cassandra, still the query language used by Cassandra is highly precise. It’s CQL (which is modeled in the line of SQL). The functions and features of CQL are significantly more extensive than those of the HBase query language.

HBase vs Cassandra: When to use what?

Use HBase if you need consistency in large-scale reads and if you do a lot of batch processing, and MapReduce if you want to work with HDFS directly.

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