How to Adapt to Changes and Process Big Data Sets Faster
NoSQL Databases were first developed in the early 21st century to pick up where relational databases, first developed in the 1960s, left off. They are known for being non-relational, open-source, distributed, and scalable.
They meet the next level of data load and the new form modern-day data takes. NoSQL database models like the document model enable greater flexibility and shorter release cycles with their schemaless features.
Most NoSQL databases are not fully transactional (ACID), but some like MongoDB and RavenDB are ACID across multiple-documents and throughout the entire database cluster, enabling business applications to use the latest database technology.
Developers use NoSQL databases to process a massive amount of data at high levels of performance. NoSQL database systems go beyond the legacy SQL tabular models to take in unstructured data, which compromise 80% of all data processed.
NoSQL is the go-to database for big data and real-time applications, offering real-time data replication, clustering, and high availability with unsurpassed zero downtime for clients if a server goes down.
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Advantages of NoSQL
Compared to relational database systems, NoSQL databases can process more data in less time. Document Databases can take in data whole, where SQL versions have to break it down into tables. For each query, they have to put tables back together before serving up the results.
In a distributed database system, this can raise complexity to red levels. It also means that slow queries make users wait as the database works to join the tables together. RavenDB has consistently proven to reduce the latency of complex queries by about 1000% when compared with relational counterparts. A NoSQL database that can take in all the necessary data in a document form keeps things simple, enabling you to scale out and expand your database cluster while managing complexity effectively.
- A Schemaless database shortens your release cycle, keeping your application truly agile.
- A NoSQL model lets you get started a lot sooner.
- A distributed database allows for data replication and assignment failover of backup tasks to reserve nodes, resulting in higher availability.
- NoSQL databases are ideal for processing unstructured data at high speeds.
- NoSQL databases are great for business applications that strive to serve the customer as quickly as possible.
NoSQL Database Models
Today’s data comes in different shapes, forms, even platforms. NoSQL databases are for the age of mobile devices and the cloud, where data can come from any location on earth. Newer data models have adapted for these changes to make managing today’s data a snap and to seize the opportunities of today’s information landscape a lot simpler.
Document Database: This model is the most popular among developers. A document database stores hierarchical JSON data. Unlike relational models, there is no impedance mismatch, so this type of NoSQL database maps very well to programming languages’ object graphs. A document database has all the information you need in one place. Adding an index to your documents, along with skipping the step of putting together tables gives you lightning speed database performance.
Graph API: Organize large volumes of data into meaningful patterns to peek into the future. You can track the relationships all your data points have with one another to process, aggregate, and index this new data set in real-time. Graph API has been used effectively for trading algorithms in hedge funds, health care applications, fraud detection, and more.
Key-value store: A type of NoSQL database that stores data in simple key-value pairs. Used for handling lots of small, continuous, and possibly unpredictable reads and writes. Some support more sophisticated data structures, including lists, sets, counters, and maps.
Distributed counters: This data model employs multiple servers to handle the aggregate load. A good NoSQL Database will add numbers without having to lock your system each time it increments. The document itself doesn’t lock because the counter is not technically part of the document. This increases performance by enabling your system to take in all the increments at once.
Achieving ACID Transactions with a NoSQL Database
To achieve the high-performance NoSQL databases aim for, most NoSQL Databases will sacrifice ACID data consistency. Among those that do include fully-transactional features, it comes at a considerable cost to performance.
Some NoSQL databases can give you everything to take in new kinds of data at unprecedented loads while maintaining ACID guarantees and high performance. RavenDB is among the few NoSQL database solutions to offer ACID both across multiple documents and throughout your database cluster while continuing to deliver the high-speed NoSQL databases promise.
Get the best of all worlds for business applications:
- High performance
- Easy scalability
- Reduced latency
- The highest standards of data integrity
RavenDB vs MongoDB: Which is Better for You?
Over the past ten years, both RavenDB and MongoDB have evolved in their own direction, offering a unique set of answers to today’s data challenges.
See how the top two solutions in the NoSQL Database sector square up to decide which one is right for your next project.
- How well each database prevents data loss
- How fast is each database
- How each database protects your data from hacking
- How easy it is to set up and to use each database
- How effectively each database replicates and distributes your data
- How well each database works with current or legacy SQL solutions
- How many third-party applications each database requires
- Indexing, caching, aggregating, concurrency, and more…
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