Introduction to Apache Cassandra
Last updated on: 2021-06-17
Authored by: Satyakam Mishra
This article presents an overview of Apache Cassandra®, an open-source, key-value NoSQL database.
Prerequisites
For an introduction to NoSQL databases, see the following articles:
Benefits of using Cassandra
Using Cassandra provides the following advantages:
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Cassandra is high-performing and horizontally scalable. It also offers operational simplicity.
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Cassandra is fully distributed, with no single point of failure. Full distribution enables Cassandra to provide continuous availability.
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Cassandra uses a peer-to-peer distribution model that makes distributing data across multiple data centers and cloud availability zones easy.
Cassandra uses a partitioner, or partitioning key, to determine how to distribute data across the nodes that make up a database cluster. A partitioner is a hashing mechanism that takes a primary key of a table row, computes a numerical token for it, and assigns it to one of the nodes in a cluster. While Cassandra has multiple partitioners from which to choose, the default partitioner randomizes data across a cluster and ensures an even distribution of all the data. In addition, Cassandra automatically maintains the balance of data across a cluster even when you remove existing nodes or add new nodes to a system.
Cassandra is a good choice when you have a very large amount of data and consistency isn’t a priority.
Terminology and concepts
Many concepts in Cassandra have close analogies to concepts in relational databases such as Oracle Database®. The following table compares the basic terminology and concepts:
| Cassandra | Oracle Database |
|---|---|
| Keyspace | Database/schema |
| Table | Table |
| Row | Row |
| Column | Column |
| Primary key | Primary key |
Feature comparison
The following table compares the features of Cassandra with the features of Oracle Database:
| Feature | Cassandra | Oracle Database |
|---|---|---|
| Rich data model | Yes | No |
| Dynamic schema | Yes | No |
| Typed data | Yes | Yes |
| Data locality | Yes | No |
| Field updates | Yes | Yes |
| Easy for programmers | Yes | No |
Query language
Both Cassandra and Oracle Database have their own rich query language.
However, there are some differences between them. To handle advanced
queries, Oracle Database supports procedures and functions for
manipulating the data returned from the SELECT statement. In contrast,
Cassandra uses the Cassandra Query Language (CQL). This language runs
through the Cassandra shell, which is called cqlsh.
The following table provides a few examples of how CQL statements and SQL statements differ:
| Cassandra (CQL) | Oracle Database (SQL) |
|---|---|
| INSERT INTO users (first_name, last_name, display_name) VALUES (‘Lebron’,‘James’,‘KingJames’); |
INSERT INTO users (first_name, last_name, display_name) VALUES (‘Lebron’, ‘James’, ‘KingJames’); |
| SELECT * FROM users; | SELECT * FROM users; |
| UPDATE users SET state = ‘TX’ Where user_uuid=88b8fd18-b1ed-4e96-bf79-4280797cba80; |
UPDATE users SET status = ‘C’ WHERE age > 25; |
Source: Datastax. DSE 5.1 Administrator Guide.
Can you use Cassandra and Oracle Database together?
Yes. There are many examples of hybrid deployments of Cassandra and Oracle Database. In some cases, new business requirements push organizations to adopt Cassandra so that they can incorporate next-generation components into their applications.
For example, both Cassandra and Oracle Database use conditional entry updates, composite keys, Unicode characters, and full-text search. However, Cassandra also has auto-replication functions that automatically distribute and maintain data across a cluster. Replication in Cassandra is very straightforward and simple to configure and maintain.
While Oracle Database uses the ACID (Atomicity, Consistency, Isolation, Durability) integrity model, Cassandra offers the AID portion of ACID, in which the data written is atomic, isolated, and durable. The AID model enables Cassandra users to decide exactly how strong data consistency should be for a transaction or set of batched transactions batched. The strength of data consistency refers to whether all nodes must respond or if a single node responds while the others update.
Cassandra users can tune data consistency within a single data center or across multiple data centers. However, Oracle Database offers integrity features that Cassandra doesn’t offer, such as isolation, transactions, referential integrity, and revision control.
Both Cassandra and Oracle Database are horizontally scalable and support data replication.
Limitations of Cassandra
While there are several advantages to using Cassandra, there are also limitations that make Cassandra unsuitable as a general-purpose database. For example, because Cassandra doesn’t have built-in aggregation functionality, it does not group data by sum, min, or max. You have to pre-compute and store any aggregations.
In addition, you can’t join tables in Cassandra. Instead, you have to de-normalize data before storing it in the database.
Finally, Cassandra bases search on keys and indexes only. It does not support additional search clauses, additional conditions, or sorting on non-key fields.
Next step
Choosing between an RDBMS and NoSQL
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