This blog post is a continuation of the thought leadership series to evangelize stream processing in the data processing space. In this blog post, we highlight the core differentiators that provide clear value to users.
RisingWave differentiates itself in the stream processing market with its innovative approach, rooted in a unique combination of core design principles. By incorporating these principles, RisingWave offers clear value to users, setting it apart from competitors and providing a distinct advantage in the data processing space.
Core differentiators of RisingWave
RisingWave unifies all event data processing and serving in a single system
Most competitive stream processing products utilize different compute services for stream processing, data management and data serving. For example, Flink specializes in stream processing but relies on other datastores for serving real-time data, which may not be optimized for that purpose.
Similarly, traditional platforms like Spark and Snowflake started with batch processing and added stream processing later, resulting in duplicated data and increased operational overhead.
In contrast, RisingWave is designed with a focus on promoting ease of use and cost efficiency, making stream processing accessible to startups, SMBs, and larger enterprises.
A unified batch and stream processing architecture with built-in serving layer is crucial because it enables seamless integration of real-time data processing within a single framework. This eliminates the need for redundant data platforms, reducing complexity and cost, while improving efficiency and the ability to handle diverse data workloads. Such a unified approach supports a more agile and responsive data strategy, essential for modern data-driven decision-making.
Why does this matter?
Data freshness. Having data in a unified streaming database offers valuable benefits, especially in providing real-time context to business users when they need it. Let's consider a security incident tracking system as an example. With new code being deployed daily, incidents can be unique and constantly evolving. RisingWave's essence lies in delivering immediate insights to investigators without the added latency caused by a fragmented architecture. In contrast, tools that rely on fragmented data often hinder investigations, requiring experts to manually connect the dots between different databases based on their intuition and experience.
RisingWave provides an easy on-ramp for new users by offering Postgres compatibility
In the stream processing market, first-generation products require users to learn a new API for data processing. While this may suit early adopters who are typically more advanced users, it creates a high barrier to entry for other users wishing to adopt the technology. Users shouldn't have to spend countless hours learning the nuances of new data processing APIs or designing complex schemas to make their data useful.
With the increasing adoption of stream processing by many companies, it has become crucial for stream processing platforms to align with the existing capabilities of developers. RisingWave recognized this need and took a different approach. We wanted users to be able to get started quickly and leverage their existing skills. However, we didn't stop there. We ensured that RisingWave integrates smoothly into an existing ecosystem. There’s no data ecosystem more popular than Postgres with its rich collection of tooling as well as deep integration with a wide range of data platforms providing seamless integration. That's why RisingWave is wire-compatible with PostgreSQL, allowing it to seamlessly work with customers' existing tooling.
Why does this matter?
Developer velocity. PostgreSQL compatibility enables users to quickly overcome the learning curve and provides an easy entry point for writing simple code that encapsulates complex stream processing logic. For instance, those who are new to stream processing, it can be challenging to grasp the semantics of a new paradigm combined with the intricacies of a new API. Data engineers already have a lot on their plate, and our goal is to relieve them from the burden of extensive work below the "value-line" and allow their data to work for them instead.
RisingWave offers a native stream processing engine built for modern cloud architecture
Streaming data is often unbounded and can exhibit bursts of activity. This can overwhelm traditional stream processing systems that are designed with on-premises architectures in mind. RisingWave, on the other hand, is purpose-built to handle the challenges of streaming data in the cloud. RisingWave takes a modern approach by decoupling storage and compute. This means that data can be ingested into cost-effective object stores like Amazon S3, while compute resources can be scaled independently and dynamically based on the scale and complexity of customer workloads.
Why does this matter?
Cost. Legacy stream processing platforms often lack the ability to provide an elastic and scalable service architecture due to architectural constraints such as data colocation and high compute requirements. As a result, customers may try to limit the amount of data ingested or the retention periods to control costs. At RisingWave, we believe that customers should have the flexibility to ingest all the data they need without worrying about compute costs being tied to the amount of data stored. With the affordability of cloud storage, storage costs should not be a major deciding factor when implementing a modern stream processing system. We aim to provide a cost-effective solution that empowers customers to leverage their data to the fullest extent without unnecessary cost restrictions.
RisingWave offers flexible deployment and pricing options to cater to customer needs
RisingWave understands that every customer has unique requirements, which is why we provide a range of deployment choices. Users can opt for our fully managed SaaS service, self-deployed customer clusters, or the in-between hybrid BYOC (Bring Your Own Cloud) model, which is gaining popularity. In the SaaS solution, RisingWave Cloud hosts the service, while in the BYOC and self-deployed clusters, the customer's cloud is utilized. This flexibility allows customers to select the deployment model that best aligns with their data residency and regulatory requirements.
When it comes to pricing, RisingWave follows a transparent approach. We charge users separately for compute and storage costs based on their usage. We also offer various billing options, including Pay-As-You-Go, annual commits, large discounts, ensuring that we meet the diverse expectations of our customers.
Why does this matter?
Choice. Customers using legacy stream processing platforms often lack transparency when it comes to pricing. They may not have clear visibility into the resources consumed by their workloads, leading to uncertainty and potential cost inefficiencies. Additionally, some platforms have complex pricing models with various measures to track, resulting in a fixed cost regardless of usage levels. By giving choice, RisingWave is enabling more control to the customers to start their stream processing journey on their terms and scale as and when they need to.
