Solutions

Ship business value with reliable pipelines

Use Pipevia to power ELT, CDC replication, event streaming, reverse ETL and analytics engineering. Start small and scale confidently with built‑in orchestration, quality and observability.

1. Connect your sources

Pick a connector, configure credentials and sync strategy. Supports SaaS, DBs and object storage. Incremental and CDC built‑in.

2. Transform and validate

Write SQL/DSL transforms with tests and assertions. Enforce contracts and schema evolution automatically.

3. Load and orchestrate

Incremental merge and dedup. Visual DAG orchestration with retries, backoff, concurrency and priorities.

Common use cases

ELT to warehouse

From SaaS and DBs to Snowflake/BigQuery

Incremental keys and log‑based CDC
Schema change handling with auto backfills
Idempotent MERGE loads (SCD‑1) and SCD‑2 history

Streaming

Near‑real‑time pipelines

Kafka/Kinesis inputs, micro‑batching 30s–5m
Exactly‑once with checkpointing and dedupe
Event triggers: webhook, queue, file arrivals

Reverse ETL

Activate your warehouse data

Sync to Salesforce, Zendesk, Segment and more
Field mapping and transformation templates
Upsert, batch and rate‑limit controls

Analytics engineering

Modeling with governance

Works with dbt models and tests
Reusable macros and environment variables
Contracts and column‑level lineage

ML features

Feature pipelines for training and serving

Windowed aggregations and time‑travel snapshots
Slow‑moving dimensions with SCD‑2
Export to feature stores or object storage

Data quality

Trust the data you deliver

Assertions: non‑null, uniqueness, referential integrity
Freshness SLAs and anomaly detection
Failure policies: stop, quarantine, or continue

Technical capabilities

Ingestion

Over 100 connectors for SaaS, DBs and files
Log‑based CDC (Postgres WAL, MySQL binlog)
Batch and streaming modes with late data handling
Automatic schema evolution and type coercion

Transform + load

SQL/DSL transforms with macros and variables
MERGE, INSERT‑ONLY and UPSERT strategies
SCD‑2 support using valid_from/valid_to
Sampling, masking and PII redaction

Orchestration

Graph dependencies, retries with backoff
Concurrency controls and priorities
CRON, event and API‑triggered runs
Terraform, CLI and REST API

Observability

Run logs, metrics and traces
End‑to‑end lineage at table and column level
Alerting via email, Slack and webhooks
SLAs with budgets and alert thresholds

Security

SSO (SAML/OIDC) and fine‑grained RBAC
KMS‑managed encryption at rest, TLS in transit
Secrets manager integration and audit logs
Data plane in your VPC; control plane hosted

Example: CDC + merge

# pipeline.yaml
sources:
  - name: orders_db
    type: mysql
    cdc: true

transforms:
  - name: stg_orders
    sql: |
      select * from orders
      where _is_deleted = false

targets:
  - warehouse: snowflake
    table: analytics.orders
    load: merge
    keys: [id]

Customer outcomes

Faster time‑to‑insight

Days → minutes for critical dashboards
Self‑serve data for business teams

Lower run costs

Incremental syncs and push‑down compute
Smart retries and idempotent loads

Fewer incidents

Quality gates and on‑call friendly runbooks
Clear lineage to trace root causes

Implementation approach

Week 1

Discovery, environment setup and 1–2 pilot pipelines.

Weeks 2–3

Model core tables, add quality checks and dashboards.

Week 4+

Harden orchestration, add SLAs and hand off operations.

FAQ

Can you work with dbt?

Yes. We run your dbt models and tests natively with clear lineage.

Do you support air‑gapped?

We support private networking and a VPC data plane. Fully air‑gapped is available for Enterprise.

How do you price professional services?

Fixed‑scope onboarding packages or time‑and‑materials depending on complexity.

Talk to an engineer

We can help map your requirements to an architecture and rollout plan.

Start Free Trial