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3 Reasons Why You Need an Embedded, Modern Database

Today’s applications demand efficient data handling to provide users with seamless experiences. One solution that has gained prominence is the use of embedded databases, which are integrated within applications rather than relying on external servers. Different from a database for embedded systems, databases embedded within applications offer several advantages for storing data and analyzing it, especially in scenarios where performance, deployment simplicity, and data security are important.

Embedded databases, or an embedded database management system (DBMS), can serve a variety of use cases, but are especially valuable for applications that need to provide analytics capabilities. Those could include:

In this article, we'll explore the benefits of embedded databases, particularly the advantages of choosing a database with a modern, serverless architecture. We will also take a look at why traditional database approaches fall short in comparison.

 

Embedded Database

 

Inside a Modern, Embedded Database

Let's briefly examine the evolution of database architectures. Over time, databases have progressed through three major generations, each addressing specific limitations and challenges. A highly performant embedded database embraces serverless and stateless characteristics detailed in Generation 3.

 

Generation 1: Large-Scale Distributed Databases

The first-generation databases, exemplified by systems like Elasticsearch and OpenSearch, focused on large-scale data handling. These databases relied on sharding data into partitions, distributing the workload across clusters of nodes. While they offered scalability, they were inherently "stateful," with tight coupling between storage and compute. Querying or synchronization operations required reading data from disk, loading it into memory, and maintaining state, which could be resource-intensive.

 

Generation 2: Serverless Databases

The second generation introduced a serverless architecture, decoupling storage from compute. Examples include Snowflake, which embraced a shared storage layer. This separation improved scalability and reduced data replication issues, but challenges persisted in terms of ingestion and query performance. Second-generation databases still held state in compute, limiting their true statelessness.

 

Generation 3: Serverless and Stateless Databases

Third-generation databases, such as ChaosSearch, embrace a globally shared storage perspective, leveraging data storage like Amazon S3 or Google GCS. These databases not only separate storage from compute but also achieve true statelessness. In this architecture, the state of previous transactions doesn't persist, enabling nodes to work independently on any aspect of a database workload at any time. Cloud object storage serves as a point of synchronization and storage.

The advantages of this approach include a better cost/performance ratio, enhanced scalability and availability for large amounts of data (as well as support for any data model), and true statelessness for improved performance.

 

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Three Reasons to Leverage an Embedded Database

Now that we've explored the evolution of database architectures, let's look into three compelling reasons why you need an embedded, modern database.

 

1. Performance Optimization

One of the most significant advantages of embedded databases is the elimination of network communication, resulting in reduced latency and a small footprint. Local data storage enabled within the application leads to significantly lower data access latency compared to traditional client-server databases. In the latter, data retrieval involves network requests, which can introduce delays.

Embedded databases also offer faster read and write operations, because data resides on the same machine as the application. This proximity reduces the overhead of network data transfer, resulting in quicker data access.

 

2. Simplified Deployment and Management

Embedding the database directly within the application simplifies deployment for end-users. They don't need to install and configure a separate database server, reducing the barriers to entry. This results in a streamlined user experience and faster onboarding for new users.

Since the database is deeply integrated with the application, updates and maintenance become more straightforward. There are no external dependencies to manage, making it easier to ensure that the application remains up-to-date and secure. This results in lower operational overhead and easier version control and patch management.

 

3. Data Security and Isolation

Embedded databases offer enhanced data security, as they are typically not directly accessible from outside the application. This isolation reduces the attack surface, making it more challenging for malicious actors to exploit vulnerabilities. This improves the organization’s security posture and reduces exposure to external threats and data leaks.

In addition, data encapsulation within the application provides a level of data isolation. This can be especially beneficial in scenarios where data privacy and confidentiality are critical, such as handling sensitive customer information or financial data.

 

Which database architecture is best for you?

For data-driven teams, choosing the right database architecture is critical for the success of your application. An embedded, modern database like ChaosSearch can offer significant advantages in terms of performance optimization, simplified deployment and management, and enhanced data security and isolation. Leveraging these resources enables teams to provide live, real-time analytics at scale, resulting in improved application responsiveness and reduced cost and management complexity associated with retrieving data.

However, it's essential to assess your specific use case and requirements. For security-sensitive applications, hosting an embedded database yourself or relying on a trustworthy managed service with strong enterprise security controls may be the best approach.

In summary, the choice of an embedded, modern database should align with your application's unique needs and priorities. Whether you prioritize performance, simplicity, or security, understanding the advantages and limitations of different database generations can guide your decision-making process.

 

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About the Author, David Bunting

David Bunting is the Director of Demand Generation at ChaosSearch, the cloud data platform simplifying log analysis, cloud-native security, and application insights. Since 2019 David has worked tirelessly to bring ChaosSearch’s revolutionary technology to engineering teams, garnering the company such accolades as the Data Breakthrough Award and Cybersecurity Excellence Award. A veteran of LogMeIn and OutSystems, David has spent 20 years creating revenue growth and developing teams for SaaS and PaaS solutions. More posts by David Bunting