Big data databases collect, organise, and store large volumes of data. Big data refers to data that is large in size, varied in type, and fast-moving. It includes structured, semi-structured, and unstructured data formats.
The main benefit of big data databases is their ability to quickly ingest and process petabytes (1,024 terabytes) of data. Unlike traditional SQL databases, they are not restricted to fixed tables and columns, allowing them to handle complex data sets more efficiently.
What Is Big Data?
Big data refers to data generated rapidly in large volumes and various types. It comes from many more sources and at a much faster pace than traditional data sets.
The key characteristics of big data warehouses are:
- Volume: Individuals and organisations produce more data than ever before. This data comes from multiple sources like social media feeds, online transactions, and IoT devices.
- Velocity: This is the speed at which data is generated, received, and acted upon. Big data databases can process large amounts of data quickly, allowing for real-time or near real-time decision-making.
- Variety: Big data includes many types of data, such as text, audio, video, images, geospatial data, and 3D-generated content. Different sources produce different types of big data. For example, semi-structured data comes from mobile apps, emails, and IoT devices, which have a structure but aren’t confined to fixed tables and columns.
Each type of big data requires specific tools and databases for processing, analysis, and action. As big data evolves, the number of solutions will continue to grow.
What Are Big Data Databases?
Big data databases are non-relational databases. They store data in formats other than relational tables. These databases are designed to handle structured, semi-structured, and unstructured data. Unlike data lakes, which store data of any type without structure, big data databases organise data to make it queryable and are optimised for analytics.
These databases have a flexible schema. Fields can differ from one another and accommodate various data types. They can also be horizontally scaled, distributing workloads across multiple nodes. This is possible with non-relational databases because they are self-contained and not relationally connected.
The four most common types of distributed databases are:
- Document Databases: Store data in documents, which are records with information about an object and related metadata. These documents use field-value pairs, where values can be objects, strings, numbers, dates, or arrays.
- Key-Value Databases: Store data in a key-value format. To retrieve a value, you type in its unique key. Values can be basic objects like strings and numbers, or more complex objects.
- Wide-Column Stores: Store data in dynamic columns, which can be spread across multiple nodes and servers. Unlike relational databases, column names and formats can vary with each row. Data is stored in columns, making it quick to find specific values.
- Graph Databases: Store data in nodes and edges. Nodes contain identifiable information about an object, like a person’s name, while edges store information about relationships between nodes.
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What Are the Advantages of Big Data Databases?
Big data databases offer many benefits for data science services. They can process complex data sets that relational databases cannot handle. They also manage large volumes of different data formats from multiple sources and take full advantage of cloud and edge computing due to their scale-out architecture.
- Store and Process Complex Data Sets: Big data technologies manage structured, semi-structured, and unstructured data. This helps businesses make sense of their data, as it resembles how it appeared in the application that generated it.
- Easy to Scale: Big data databases handle large volumes of varied data better than relational databases. Data storage and processing are spread across multiple computers. As more data is added, more computers can be included to meet the increasing demand.
- Cloud and Edge Computing: Big data databases are designed for cloud and edge computing. This allows businesses to transfer some or all of their data processing to the cloud and the edge. This enables the building, testing, and deployment of applications on a hybrid or multi-cloud model.
What Are the Disadvantages of Big Data Databases?
Despite the benefits of NoSQL databases, there are challenges with big data. The lack of standardization can make these databases hard to set up and manage. Many big data databases do not support ACID (Atomicity, Consistency, Isolation, and Durability), which complicates ensuring accurate processing of database transactions.
- Lack of Standardization: Most NoSQL databases use their own schemas or none at all. For businesses, understanding each NoSQL database’s strengths and weaknesses can be time-consuming. This results in significant effort spent on pre-selection and integration into existing workflows.
- Inconsistent ACID Transactions Support: ACID properties are used by SQL databases to ensure proper online transaction processing. For example, Atomicity ensures that a multi-step process, like transferring money between bank accounts, stops if any step fails. Without such properties, extra measures are needed to ensure the data from a NoSQL database is trustworthy.
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How to Choose the Right Big Data Database Provider
When choosing a big data database, consider the size, type, and variety of the data you want to collect. Other important factors include security, compatibility with your existing systems, and your business goals.
Define Your Goals
Decide what kind of data you want to collect and what you want to do with it. If you plan to collect data from multiple processes and microservices in an application, use a key-value database. These are great for storing data that doesn’t have complex relationships. However, if you want to uncover complex and hidden relationships between different data sets, use a graph database. This will help you identify those relationships and make smart business decisions.
Choose Skilled Personnel
Ensure the people you select to develop and manage your database solution are highly skilled. They should have the relevant knowledge and experience with the specific big data database you need. Understanding how to build, test, and maintain data architecture is crucial. They should also be familiar with programming languages and know how to analyse big data.
Strong Communication Skills
Choose a provider with strong communication skills. This will make it easier to express your needs, monitor their progress, and understand the insights they provide. The provider should be easy to understand in all forms of communication, including text, email, video chat, and in-person meetings. They should also be able to explain the technology behind your big data database and the insights it generates in simple terms.
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Unlocking Deeper Insights with Big Data Databases
Businesses and organizations worldwide, regardless of size, are leveraging big data databases to gain deeper insights into their products, services, customers, and operational processes. This allows them to uncover previously inaccessible insights, enabling quicker and more informed decision-making.
If achieving these outcomes resonates with your business or organization, consider partnering with a trusted big data database solutions provider. They can assist in defining your business goals, recommending the optimal big data database solution, and managing its development, deployment, and maintenance.
For customized software outsourcing services tailored to your big data database requirements, contact us at EZtek Software. Specializing in big data, our dedicated team of experts can design, build, deploy, and manage a bespoke big data database solution that aligns perfectly with your needs. Our consultants bring deep expertise in big data technologies, machine learning, artificial intelligence, and other advanced technologies to maximize the potential of your database solution. Reach out today to discover how we can empower your business with big data.