In today's data-driven world, organizations are continually seeking more efficient and scalable ways to manage and process their data. Streaming databases have emerged as a pivotal component in this quest for real-time data insights. Last week we have published a blog discussing popular streaming databases. However, with the plethora of streaming database services available in the cloud, selecting the right one for your specific needs can be a daunting task. In this comprehensive article, we will delve into the intricate details of choosing a streaming database service in the cloud, providing you with a detailed comparison that will empower you to make an informed decision for your data-centric endeavors.

First let’s list out some popular vendors with cloud offers.


KsqlDB is a specialized database optimized for handling streaming data and assisting developers in constructing applications that process data streams using Apache Kafka. It is deeply integrated with Apache Kafka and is built on top of Kafka streams.

A significant advantage of ksqlDB is its support for SQL interactions, allowing users to directly create tables. Additionally, it enables the creation of materialized views, tables that continuously and incrementally update aggregate calculations as new data streams in. This ensures quick query responses and guarantees that rows associated with a particular key are located in the same partition.

As a cloud service, ksqlDB Cloud Service is a component of Confluent Cloud. It is a fully managed service available on the Confluent Cloud, and it is fully integrated with other products reside on Confluent Cloud, such as Stream Designer, Connectors, Schema Registry, Stream Governance, etc.


Powered by RisingWave, RisingWave Cloud offers a managed service that provides you more flexibility, reliability and scalability for your cloud-native streaming applications. In particular, RisingWave Cloud holds the following key advantages:

  • Managed Services: RisingWave Cloud offer managed RisingWave services that offer robust high availability and failure recovery solutions. RisingWave cloud will automatically handle routine maintenance tasks such as backups, patch management, and security updates. This offloads the operational burden from your IT team, allowing them to focus on more strategic tasks.
  • Scalability and Cost-Efficiency: RisingWave Cloud can easily scale up/down/in/out your RisingWave clusters to accommodate changing workloads and storage needs. With our innovative compute-storage decoupled architecture, RisingWave Cloud achieves extreme cost-efficiency comparing with other vendors.
  • Security: RisingWave Cloud invest heavily in security measures under SOC2 compliance. No more worry about data leakage.
  • Rapid Deployment: RisingWave Cloud provides very user-friendly experience so that customers can provision and manage their RisingWave clusters easily and quickly. The package of builtin monitoring tools, web query editors and source/sink integrations putting together delivers an one-stop development solution.
  • Solid and speedy technical support: Backed by RisingWave creators, our experts provide all necessary enterprise-grade technical supports in any time zone.

RisingWave Cloud is public available. Its GA release was announced in June 2023. Visit to get access to RisingWave Cloud.


Materialize is a streaming database that leverages SQL for processing. It is compatible with PostgreSQL, allowing it to integrate with numerous systems that already have PostgreSQL integration. One of its key features is its ability to automatically refresh materialized views in a consistent manner, enabling users to query data in these views concurrently. Materialize is built upon the foundation of Timely Dataflow, a Microsoft research project developed to support incremental and iterative processing. To achieve fault tolerance, Materialize employs a hot-standby model. While the source-available version of Materialize operates as a single-node in-memory database.

Materialize Cloud is a recently launched, it is designed to be distributed and cloud-native, sharing a similar design with Snowflake. Materialize Cloud offers a variety of cluster size ranging from 3XSmall to 6XLarge, adapting to different workloads of customers’ needs. It also supports high availability by active replication, i.e. running the same workload on different cluster replicas to endure hardware failures.


Timeplus is a data analytics platform designed with a focus on streaming-first analytics. It provides a range of capabilities that enable organizations to process both streaming and historical data quickly and intuitively. The platform empowers data and platform engineers to unlock the value of streaming data using SQL.

Beyond being just a streaming SQL database, Timeplus offers a complete suite of analytic functionalities. These include various data source connections, an interactive web client for real-time data analysis, real-time visualizations and dashboards, and an API for data interaction and sending analytic results to downstream data systems. It also enables setting up alerts for real-time actions based on anomalies detected in the streaming analytic results.

Timeplus cloud service is now public available. It is a pure SaaS based solution, in which users don’t need to worry about configuring the underlying resources.


DeltaStream is a stream processing platform designed to facilitate the development and deployment of streaming applications. It is built on Apache Flink, an open-source stream processing framework. This platform offers a unified SQL interface, which allows users to query and process streaming data using standard SQL syntax. This feature is particularly useful for those familiar with SQL, as it eliminates the need to learn a new language or syntax for stream processing.

DeltaStream cloud service is now available upon request. The cloud service offers more enterprise functionalities such as workload isolation, push notifications, developer API and CLI, RBAC and secure data sharing.

How To Choose?

Choosing the right cloud streaming database for your organization's needs is a crucial decision, as it directly impacts your ability to handle and analyze real-time data efficiently. Here's a detailed guide on how to make an informed choice:

  1. Define Your Use Case: Start by understanding your specific streaming data needs. Consider what types of data you'll be working with, the volume of data, and the velocity at which it arrives. Determine whether you need real-time analytics, monitoring, or historical data storage.
  2. Data Model and Schema Flexibility: Determine if the streaming database supports the data model you require. Some databases offer schema evolution, which can be beneficial for handling evolving data structures common in streaming use cases.
  3. Integration Capabilities: Check if the database seamlessly integrates with the modern ecosystems, such as development tools and, cloud infrastructure vendors, source connectors, and sink connectors. Compatibility is crucial for efficient data flow.
  4. Scalability and Performance: Assess the scalability of the streaming database. Does it offer horizontal scalability to handle increasing data loads? Evaluate its performance under heavy workloads and ensure it meets your latency requirements. Additionally, think about how your streaming data needs might evolve in the future. Choose a solution that can scale and adapt to your organization's changing requirements.
  5. SQL Support and Ease of Use: Evaluate the ease of querying and managing the database. Many streaming databases provide SQL-like interfaces, which can simplify development and make it accessible to a wider range of users. Be sure checkout the SQL compatibility as not all product have full SQL support, especially on joins and SQL functions.
  6. Deployment model. Different cloud services provide different deployment modes covering a range of different resource requirements, pricing offer, and security requirement. There are largely three categories of deployment modes:
    1. Dedicated service. The cloud service vendor provide dedicated resources for a single user. The user is aware of the resource provision and management.
    2. Serverless. The underlying resources can be scaled automatically and elastically.
    3. SaaS. The user has no control over the resources. The cloud service provide the stream processing functionalities directly.
    4. Bring your own cloud (BYOC). The software is deployed in the users’ cloud environment hence data storage and computation are carried out by the resources on users’ cloud directly. The cloud vendor only manage the resources remotely from a centralized control plane.
  7. Community and Enterprise Support: Assess the availability of community support and vendor-provided enterprise support. If the product is open-sourced, a strong open-source community can be a valuable resource for troubleshooting and knowledge sharing.
  8. Security and Compliance: Ensure that the streaming database adheres to your organization's security and compliance requirements. Features like encryption, authentication, and access control are critical.

By carefully considering these factors and conducting thorough research and testing, you can make an informed decision when choosing a cloud streaming database that aligns with your organization's real-time data processing needs.

Featured Comparison of these popular cloud streaming databases


Choosing a streaming database in the cloud requires a thoughtful approach.Start by assessing your specific needs and objectives. Consider factors such as the volume and velocity of data, real-time processing requirements, and the complexity of your queries. Next, evaluate the scalability, performance, and compatibility of the streaming database with your existing infrastructure and tools. Cost considerations are crucial, so understand the pricing model, including data storage and data transfer costs. Additionally, look for a database that provides robust security features, compliance with data regulations, and reliable customer support. Finally, consider the community and user base around the database, as a thriving community often translates to valuable resources and support. By carefully weighing these factors, you can make an informed choice that aligns with your organization’s streaming data processing can make an informed choice that aligns with your organization’s streaming data processing needs.

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