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production-ready Data-Flow Platform on Kubernetes

We automate production-ready data platforms in your cloud so you can focus on core work.

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blueprint solution bloc library stack deployment into your cloud provider

Creating cloud based Data Flow solutions at scale is challenging!

Creating a production-level solution to move data at scale takes a lot of work, from integrating many open source technologies, setting up and integrating all of the different components. It's a challenge to scale and difficult to troubleshoot. snapblocs can help you spend less time on infrastructure work, freeing up more time and resources to deliver projects that achieve your business goals.

Deploy your Data Flow solution in minutes!

There is no need to endure complex architectural design, installation, configuration, or scripting. Just click to create your Data Flow Platform on Kubernetes and let snapblocs automate the rest! 

  • Simplify your Data Flow implementation
  • Process real-time streaming or bulk data at volume
  • Self-Service no-code - DevOps can automate provisioning
  • Full lifecycle management - start, update, terminate, pause, resume, clone, move, etc.
  • Built-in Elastic Observability = logging, metrics, Application Performance Monitoring (APM)
  • Deploy into your cloud, control your infrastructure and data

Reduce your development time, free up resources, and focus on more important work!

Choose the Data Platform you need for data ingestion, replication, and synchronization

Depending on your needs, you can deploy Data Flow with all the bells and whistles or just the minimum Kafka-only solution bloc.

Focus on what you do best

snapblocs dpStudio automates many data platforms on Kubernetes, including Data Flow. 

  • No-Code, lowers skill requirements
  • Deliver projects faster, better
  • Free up scarce resources
  • Focus on your core work
  • Less tech debt

snapblocs automates architecture

snapblocs automates based on the "well-architected" guides such as "AWS Well-Architected for AWS" and Google "Cloud Architecture Framework." for the provisioning and configuring of production-grade Kubernetes clusters and workload deployment into the clusters.

snapblocs No-code Architecture-as-a-Service

Architecture-as-a-Service: The Evolution of Cloud Computing as a Service

No-code Architecture-as-a-Service: The Evolution of Cloud Computing “as a Service”. Read the article

Cloud platform evolution

Discussing Architecture-as-a-Service

Pavan Belagatti, the award-Winning Tech writer, discusses our vision for no-code Architecture-as-a-Service. Read Pavan's post

snapblocs Architecture-as-a-Service delivers instant value

Day 2 level operations out of the box

  • High availability
  • Data protection
  • Data security
  • Monitoring
  • Configurable alerts
  • Health checks
  • Cost optimization
  • Easy debugging of topic data
  • Easy overriding of Kafka parameters
  • Scaling on demand
  • Graceful shutdown
  • Pause, Resume cluster without data loss
adding value to confluent kafka on Kubernetes in the cloud

snapblocs Data Flow Platform includes

snapblocs Data flow blueprints combine multiple best-in-class open-source technologies into ready-to-go solution-blocs on Kubernetes.

 Amazon EKS - Google GKE - Microsoft AKS

Depending on which cloud provider you use, Amazon's EKS, Google's GKE, or Microsoft's AKS is utilized to provision snapblocs Data Flow Platform instances into your cloud account. 

 Kubernetes

Kubernetes container orchestration system for application deployment and scaling

Kubernetes is an open-source container-orchestration system for automating application deployment, scaling, and management. It is used to deploy selected Components.

 Kafka

Kafka streaming real-time data pipelines

Kafka is used for building real-time data pipelines and streaming applications by integrating data from multiple sources and locations into a single, central Event Streaming Platform.

 Elastic

Elastic observability for monitoring and alerting and application performance monitoring

Elastic is used to provide observability (monitoring, alerting, APM) for answering questions about what's happening inside the system just by observing the outside of the system.

 Grafana

Grafana data visualization

Grafana is used to build visualizations and analytics to query, visualize, explore metrics, and set alerts for quickly identifying system problems to minimize disruption to services.

 StreamSets Data Collector

Streamsets Data Collector for data ingestionn pipelines

StreamSets Data Collector creates continuous data ingest pipelines using a drag and drop UI within an integrated development environment (IDE).

 Apache Nifi

Apache Nifi Data processing and distribution

Apache Nifi is used to create a data processing for data transforming, routing, curation.

Example Data Flow use cases

Data Flow is the perfect solution when you need reliable data movement from input data sources to your target data destinations via stream mode or bulk mode for data ingestion, replication, and synchronization.

 General

Process and analyze streaming data to provide real-time insights and actionable intelligence. Create new products and services or improve business operations.

  • Messaging
  • Event sourcing
  • Website activity tracking
  • Log aggregation
  • Commit log
  • Stream processing

 Stream Data Ingestion

Ingest data in real-time as they arrive. Good for real-time data-driven decision processing for improving customer experience, minimizing fraud, and optimizing operations and resource utilization.

 Bulk Data Ingestion

Ingest blocks of data that have already been stored over a period of time. It is often used when dealing with huge amounts of data and/or when data sources are legacy systems that cannot deliver data in streams. Bulk ingestion is suitable when:

  • Data freshness is not a mission-critical issue
  • You are working with large datasets and are running a complex algorithm that requires access to the entire batch – e.g., sorting the entire dataset.
  • You get access to the data in batches rather than in streams
  • When you are joining tables in relational databases

 Data replication

Replicate data from one data repository to another data repository. For example, replicate MySQL data to Postgres in real-time using Change Data Capture.

 Data Synchronization between data centers & clouds

Synchronize datasets from one data repository to another or between multiple data centers or Clouds.

Get instant Day-2 Level Operations 

Self-service fully automated Kafka clusters deployed in your cloud environment. Click to deploy, scale at will. 

  • Self-service for DevOps and agile teams
  • Automated Day-2 operational Kafka clusters
  • Best practice security, dashboards
  • Configure, deploy, manage and monitor
  • Pause, resume, clone, scale
  • Built-in observability
data Platform solution blocs lifecycle management

snapblocs Data Flow Platform compared

The reality of DIY Data Platforms

Building your Data Flow solution and going from POC to production requires a significant investment from multiple engineers over many months. 

  • Effort and resources are underestimated
  • Project timelines become extended
  • A lot of reinvention reduces time on core work
  • Knowledgeable resources are scarce
  • Security and dashboards are often inadequate
  • Full-featured solution not feasible for small IT teams

Hosted Data Flow solutions?

Hosted managed Data Flow solutions promise simple turnkey solutions, but data becomes spread across more data locations. 

  • Increased data movement in/out of vendor VPCs
  • Creates privacy, security, latency, and cost issues
  • Not as cost-effective with  high event volumes

snapblocs Data Flow Platform vs other vendors comparison chart

snapblocs
Data Flow
Platform
Azure Data
Factory

Informatica Cloud
Integration

Oracle Data
Integrator 

SQL Server
Integration
Services

Google Cloud
Dataflow
Apache Nifi

Confluent
Kafka Platform,
Community Edition

Pentaho
Data Integration
Kettle (
 ETL ) 

StreamSets
Data Collector

Talend Open
Studio
Self-service provision to cloud
Yes Yes No
No vendor lock-in (Open source) Yes No Yes
Multi-cloud Yes No Yes
Run on Kubernetes Yes No Manual installation
Loosely coupled architectures Yes No No
Lower risk for integrating other open-source Yes No No
No-code for data pipeline Yes Yes Yes
No (Confluent Kafka Platform)
SaaS delivery Yes Yes No
Agile delivery Yes No No
Expanding range of use cases Yes Limited Limited
Full lifecycle features* Yes No No
Built-in observability Yes Yes Minimum or none
Pay-as-you-go Pricing Model Yes Yes / No Yes / No
Development effort Small Small Large
Recurring license / subscription fees Small Medium-large None
Skills & resources Modest Modest Many skills & resources required
Large number of sources and destination connectors High ,
NiFi +
Streamsets DC +
Kafka Connector
High Low
Handle backpressure Yes Yes / No Yes / No

* Powerful lifecycle features like pause, resume, clone, and move the Kafka cluster

snapblocs architecture as a service solution blocs

Leverage additional snapblocs platforms

snapblocs offers a pre-fab blueprint library that combines multiple best-in-class open-source technologies into ready-to-go solution-blocs on Kubernetes

  • Data Platforms for Moving, Ingesting, Transforming, Processing, Storing, Analyzing, and Presenting data.
  • PLUS, Development Platforms for Kubernetes and Microservices.

snapblocs makes it easy to Deploy and Manage Data Platform stacks

How to deploy a stack

This video will explores Component Configuration, Stack Deployment and Stack Teardown.

How to manage the lifecycle of a stack

This video demonstraights Pausing, Resuming, Cloning and Moving stacks.

snapblocs SaaS based dpStudio supports multi-Cloud

snapblocs dpStudio supports the major cloud providers, including Amazon Web Services, Google Cloud Platform, and Azure.

Leverage our Data Flow Platforms on Kubernetes as an infrastructure abstraction: Configure once and run in any cloud.

Click to deploy, scale at will

Confluent Kafka
Confluent Kafka on Amazon AWS
Amazon Web Services - AWS
Kafka event streaming on Microsoft Azure
Kafka on Google Cloud Platform - GCP

Start your free Data Flow Platform on Kubernetes today

Deploy data flow solutions and many other data platforms using the snapblocs blueprint library.

Includes free sandbox credits

No credit card required

 Documentation

Our Help Center has the resources you need to get up and running with out no-code data platforms on Kubernetes in your cloud environment.

Access the Help Center 

 Videos

Tutorials and How-to-Videos show how dpStudio and our blueprint library can reduce your development cycle. 

View the Videos 

 Need a demo?

Schedule your free interactive demo.

Contact us

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