Invergent

BigConnectPipelines

Data Integration for Hybrid & Multi-Cloud Environments

Pipelines/sales-ingest/RunHealthy
Sources
orders2,884Kafka topic, Streaming
crm.customers672PostgreSQL, CDC
invoices/*.csv8,400S3 bucket, Batch
Transform
Parse01
Mask PII02
Map schema03
Deduplicate04

New column discount_code in crm.customers. Mapped, nothing dropped.

Destinations
warehouse.sales11,480Data warehouse
lake/raw11,956Data lake
Latency2.1 s
Errors0
01

Data Ingestion Pipelines, Simplified

Spend more time building data smart pipelines, enabling self-service and innovating without the noise. BigConnect Pipelines is an easy-to-use data pipeline engine for streaming, CDC and batch ingestion from any source to any destination.

  • Build pipelines for streaming, batch and change data capture (CDC) in minutes
  • Eliminate 90% of break-fix and maintenance time
  • Port data pipelines to new data platforms without rewrites
02

Operationalize Your Data Collection

  • 01

    Single Experience for All Design Patterns

    Build schema-agnostic smart data pipelines with pre-built sources and destinations in minutes for streaming, batch, and change data capture (CDC), using a single, visual tool.

  • 02

    Ingest Data Across Multiple Platforms

    Run your data in a development environment on multiple platforms without rework. Pipelines are platform agnostic by design so you can reuse them across data platforms in hybrid and multi-cloud environments.

  • 03

    Built for Change

    Worst case scenario: an upstream change doesn’t break your pipeline, it flows unreliable, incorrect, or unusable data into your analytics platform undetected. Intent-driven pipelines built for data drift, reducing risk of bad data downstream and outages. When data drift happens, pipelines alert you to remediate issues or embrace emergent design.

03

Typical use cases

  • 01

    Load data into data warehouses

    Import and prepare data for analysis in data warehouses with automatic transformation capabilities.

  • 02

    Ingest data into data lakes

    Ingest unstructured and object data into data lakes from many sources

  • 03

    Integrate with big data for machine learning (ML) and analytics

    Import and prepare data for use in modeling and big-data analytics with Hadoop, Kafka, JMS, NoSQL databases for ML and AI.

  • 04

    Modernize data infrastructure

    Native support for big data and AI, through the BigConnect platform integrations.

04

High-performance data transformation

  • 01

    Powerful ETL

    Boxed with features to build, monitor and debug your data pipelines.

  • 02

    Distributed

    Run pipelines in a clustered environment to accelerate your ETL flows

  • 03

    Native big data support

    Transform and execute data mappings with native BigConnect features for super-fast data transfer.

05

Out-of-the-box integrations

  • 01

    Prebuilt connectors

    Large library of technologies simplifies integrating sources and targets to give developers more flexibility.

  • 02

    Declarative design

    Create data-mapping rules to accelerate development of integration logic and increase productivity.

  • 03

    Guided integration

    Best practices to simplify data mapping between systems

06

Heterogeneous system support

  • 01

    Big data integration

    Prebuilt big data connectors for Hadoop, Spark, Hive, Kafka, HBase, Sqoop, Pig, Cassandra, NoSQL databases, and more allow users to integrate any data from any source.

  • 02

    Popular databases and other technologies

    Extensive database support, ERP and CRM systems, B2B systems, flat files, XML, JSON, LDAP, JDBC, ODBC, SaaS, and third-party appliances.

One semantic data lake, from the first record to the last report.

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