Develop, debug and run on desktop

$ 5,000

  • Supports PC/Mac/Linux
  • Hadoop/HDFS support
  • Subgraphs sharing
  • Advanced Excel connector
  • Web Services connector
  • CloverCARE Support

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Basic scheduling & Multi-user platform

  • 8 CPU cores max
  • Secure parameters
  • Execution history tracking
  • Parallel execution of transformations
  • Multi-user access/security
  • Real-time capabilities
  • Basic Scheduling

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Parallel processing & Failover Redundancy

  • In addition to Corporate:
  • 32+ CPU cores
  • 2+ nodes
  • Distributed execution / Big Data
  • Load balancing
  • Failover
  • Autoscaling

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Perpetual licensing - Pay only once

Note: 20% annual maintenance fee entitles "CloverCARE Support" access - plus two major version updates per annum.

Flexible licensing options available upon request

Training and Services Pricing

Standard Training

$ 8,000 / 3 Days

Class up to 8 people

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Covers basic concepts, reading/writing files and databases. Developing, debugging and optimizing transformations and jobflows.

Advanced Training

$ 6,000 / 2 Days

Class up to 8 people

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Enhances standard training with Server deployment, advanced data sources & target (WebServices, XML, JSON). Advanced optimization techniques.

Our training sessions include best practices guidelines with proven solutions. Offers hands-on experience and Q&A learning environment. Students receive certification post-training.

Services / Proof of Concept

74% of our customers contracted a Proof of Concept or initial services package with our team.

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Get started together with our consulting team!

We can prepare a Proof of Concept prototype and assist you developing the initial solution.

Additional modules

  • CloverETL Designer (multi-license)

    Enterprise multi-license for CloverETL Designer
    (for 10+ seats)

  • CloverETL Server Corporate Plus

    A Server Corporate package including 1 production license and 1 non-production license.

  • CloverETL Server Corporate
    (High Parallelism)

    Server Corporate with single-node Cluster enabled features works great as a stepping stone towards larger deployments enabling you to design future-proof parallel data transformations.

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