Open Source Wide Column Databases are extremely popular nowadays, especially for those companies that do not have a wish to use expensive data platforms but want to enjoy all nanotechnologies in data management. It may still not be easy to pick the right database and just get lost in a wide diversity of providers.
In this post, you will learn everything about Open Source databases, find out which of them are available to you, what types of databases exist, and which of the software companies are the most popular. You will also learn about the resources that will help you figure out much more about the databases you really need.
What is Wide Column Database
A Wide Column Database is a version of a NoSQL database with varying names and columns format. They may vary not only across rows but even within the same table. While browsing the Internet, you may come across such a name as a column family database. This is the same.
Data is stored in columns. Thus, the whole column can be searched and loaded fast due to really quick queries for a particular value. Related columns are modeled as part of the same family.
The perks of wide column databases:
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High querying speed;
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The flexibility of the data model;
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Scalability.
Wide Document Database vs Column Database
Let’s figure out the difference between a relational database system and wide-column NoSQL databases. In the first system, data is stored in a table with rows spanning a certain number of columns. In case an extra column is needed, it must be added to the whole table. In this case, null or default values are provided for the rest of the rows.
But if the table has to be queried for a non-indexed value, the process of relocating the values will be really slow.
The second type of database still has the row conception. However, reading or writing a data row means reading or writing separate columns. If there is a data element for a column, only then is it written. Each data element is referenced by the row key. Querying for a value is optimized, though.
When speaking about a column database, you should know that each column is stored separately on a disk. A wide-column datastore supports a column family that is stored together.
Wide Column Databases
One of the important features of such databases is their ability to use different column names and formats across rows. It accesses the data in the column quickly and boosts scalability, and it can be shared.
If you don’t know what the top wide column NoSQL database is, it’s necessary to learn more about Hadoop and Cassandra.
It is an original big data open-source ecosystem. Once invented, it was extremely successful. It was the way for multiple popular and accepted big data concepts as distributed ledgers and data lakes.
The system is still widely used. However, it has batch-oriented patterns. Those patterns aren’t always good for prediction and analytics. Those analytics are focused on streaming and analyzing huge amounts of data at a time.
A good Wide Column Database example is Cassandra. It was originally meant for Facebook. It can be distributed easily, as well as used in many clouds. This database management system is perfect for pairing with Spark and Kafka data solutions.
The system was designed to implement the combination of Dynamo distributed storage by Amazon and storage engine model and Bigtable data by Google.
Types of Open Source data stores
If you are not really sure of how different data stores differ from one another and what types of open source databases there exist, check the following list that should give you a much better insight into different types of Open Source data stores and their examples:
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Relational Databases (PostgreSQL, MariaDB, CockroachDB, MySQL, CouchDB, MongoDB, Jackrabbit);
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Graph Databases (Neo4j, JanusGraph);
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Key-Value Databases (Redis, Elasticsearch, etc, Couchbase);
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Wide Column Databases (Cassandra, Hadoop).
How Do Wide Column Data Stores Work?
Wide column data stores are similar to relational data stores. They both arrange data into columns. This is probably the only similarity of these two data stores’ types. Remember Hadoop and Cassandra? They are scale-focused and can store even partitioned and distributed data columns.
In wide column data stores, the attitude toward columns is also different. There is a capacity for multiple names and formats across rows. They allow for higher data compression and simplification of huge data volumes thanks to the way the data is assessed and stored.
Column Database availability attracts many companies and users, while open-source data stores are free to download, modify, and use again. Open-source databases can be used in different ways depending on the license type. The key principle is that the underlying code can be accessed and modified publicly.
How to add columns in wide-column data stores
Quite often, there is a necessity of adding an attribute to a data model after deployment. Developers often keep that in mind. Let’s say your business requires augmenting customer profiles with a new attribute for supporting a new service. While using a relational data store, you would need to add a new column to the whole table.
In this case, other rows would contain spaces. In the worst cases, the developers locate unused legacy columns for repurposing the data that didn’t match the new scheme.
While using a wide-column data store, you can simply add elements to new columns. It impacts neither the existing columns nor the data they contain.
Use cases
If you need a large dataset to distribute across many nodes, a wide-column database is perfect for this role. Here are some of their use cases:
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IoT sensor data;
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Log data;
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Attribute-based data (equipment features, preferences);
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Time-series data (financial trading or temperature information);
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Real-time analytics.
If you need a horizontal scale of your data, a wide column data storage is exactly what you need. It also provides consistency for your data. However, such databases are not suitable for all apps. In a couple of years, you can definitely see increased adoption for wide-column databases, at least for such as Cassandra.