Relevant Software
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Data ingestion services

Data ingestion services

Q: How do you keep records from being dropped or duplicated when a source spikes or an ingestion job fails?

Ingestion breaks in one of two ways under stress: a spike overruns the intake and events are dropped, or a retry after a failure loads the same records twice. Both get handled at design time. Each source gets a delivery guarantee, exactly-once or at-least-once, chosen and documented before the build. A spike is absorbed by backpressure, which buffers events until intake catches up. A failed run replays from the last committed offset, so a record lands once.To see where you stand today, force a failure in staging: kill an ingestion job mid-run and check whether the rerun double-counts. If it does, that’s the gap we close first. If you can’t safely test that yet, we run the same check against your pipelines during the audit.

Q: Our source has no API, only a database or a file export. Can you still ingest from it?

Yes, we can. An API is one access path among several. A source with only a database connection is ingested through direct queries or log-based change data capture. A source that only drops file exports is ingested by watching the drop location and landing each file as it arrives. Older ERPs and mainframes usually expose at least one of these paths.To scope it, list each source and note how you currently get data out of it: an export, a database login, a manual download. If a source has a path out, we can automate it. If you’re not sure what a source exposes, our engineers check it with you on the first call.

Q: Can you take over ingestion pipelines another team or a vendor built?

Yes, we can, and an inherited setup is a common starting point. Our team starts by auditing what runs: which sources the pipelines cover, how each one captures data, and where records drop or duplicate under load. We stabilize what works. We rebuild what fails, without a full teardown unless the audit calls for one.Ingestion is one layer of a broader data engineering practice, so if the audit shows the problem runs past intake into transformation or the warehouse, our team can take that on too. Send us what you’re running and we’ll tell you what’s worth keeping.

Q: How do you decide whether a source runs on batch, streaming, or change data capture?

The mode follows two things: how fast the data loses value, and what the source can support. A source feeding a daily report runs on batch. A feed behind alerting or live inventory runs on streaming, so events land in seconds. A database that has to stay mirrored without full reloads runs on change data capture. Where a source supports more than one mode, we choose by the latency the downstream use case needs.To sort your own sources, list each one with the question it answers and how current that answer has to be. If you have that mapping, we turn it into a mode per source. If you don’t, our engineers build it with you from your reporting and operational needs.

Q: What determines the cost and timeline of an ingestion build?

Two variables drive cost and timeline: how many sources are in scope, and how many of them are documented. A documented source on batch is quick to build. An undocumented source, or one that needs streaming or change data capture, takes longer, because our engineers have to work out the capture path first.You can size the rough shape yourself: count your sources, split them into documented and undocumented, and mark which need data in seconds and which can wait hours. If you have that list, contact us with it and we’ll return a scoped plan and cost estimate within 14 days. If you don’t have it yet, our engineers build it after the first call.

When a source’s volume outgrows the intake built for it, records get dropped before they ever reach storage. Relevant Software’s data ingestion lands every record from every source — batch, streaming, or change data capture — complete and on time.

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On-time deliveryRoadmaps you can plan around

50%

Faster delivery with AIAI-assisted, senior-reviewed engineering

Our data ingestion services

Source connector development
Batch ingestion
Real-time and streaming ingestion
Change data capture (CDC)
Reliable landing, backfill, and replay

Source connector development
Batch ingestion
Real-time and streaming ingestion
Change data capture (CDC)
Reliable landing, backfill, and replay

Source connector development

Our engineers build and maintain the connectors that pull from every system you run: REST and SOAP APIs, databases, flat files, and SaaS platforms. Each connector is documented per source, so your team can read what it does without opening our code.

Connectors for APIs, databases, file exports, and SaaS platforms, built to your source list
Authentication, rate-limit, and retry handling scoped per source
Connector logic documented per source, maintainable by your team

Batch ingestion

For sources that update on a schedule, our team builds batch ingestion sized to what each source and destination can sustain, incremental wherever the source supports it.

Incremental loads for high-volume sources, full loads where data size allows
Schedules set against source system load, so intake stays clear of production traffic
Landed volumes checked against the source before a batch is marked complete

Real-time and streaming ingestion

For data that loses value by the hour, our architects build streaming ingestion on Apache Kafka and equivalent platforms, landing events within seconds of when they happen.

Event streaming intake for low-latency cases like alerting and live inventory
Backpressure handling that holds a source spike in a buffer and keeps every event
Ordering and delivery guarantees defined per stream

Change data capture (CDC)

To keep a destination current without reloading entire tables, our engineers set up change data capture that streams inserts, updates, and deletes from your source databases as they occur.

Row-level capture of inserts, updates, and deletes from source databases
Log-based capture, so intake stays light on the source system
Deletes captured and applied, so the destination drops records the source has removed

Reliable landing, backfill, and replay

Our team lands raw data into your lake or warehouse with delivery guarantees that hold under failure: no dropped records, no duplicates, and a replay path for any window that fails.

Exactly-once or at-least-once delivery, chosen per source and documented
Schema drift caught at intake, so a changed source leaves the raw layer intact
Backfill and replay for any window, without re-ingesting everything

Where data ingestion fits in your data stack

Data ingestion lands the raw data
Connecting to every source and landing complete, current data in your lake or warehouse, before anything transforms or reconciles it.
Data integration makes sources agree
Reconciling conflicts once sources are landed, deciding which system holds the correct value, covered on data integration services.
Read More →
Data pipeline development runs it in production
Orchestrating, scheduling, and monitoring the full flow across every pipeline, covered on data pipeline development services.
Read More →

Your warehouse can track every insert, update, and delete in a production database, without a nightly full reload. Tell us which database you run and we’ll map the change data capture path for it.

How our data ingestion engagement works

A source inventory and access map
Every source gets documented with its access path, volume, and latency need, so the intake plan matches what each one can actually support.
Connectors built and documented
Connectors get built per source and handed over as documented code, readable by your team from the first commit.
Delivery guarantees tested against real failure
Exactly-once handling and replay run against induced failures and volume spikes, so the guarantee holds before it reaches production.
Landing verified against the source
Landed record counts get reconciled against the source, and your team reviews the match before intake goes live.
Production handoff with monitoring in place
Ingestion goes live with schema-drift and freshness monitoring, plus runbooks your team runs without us.

How our <b>data ingestion engagement</b> works

Our data ingestion tech stack

Sources & connectors
REST/SOAP APIs, databases, flat files, SaaS platforms, Airbyte, AWS Glue
Streaming & real-time
Apache Kafka, Apache Flink, Apache Beam
Change data capture
Log-based capture streamed through Apache Kafka
Cloud ingestion services
AWS Glue, Azure Data Factory, Google Cloud Dataflow
Landing & destination
Snowflake, BigQuery, AWS Redshift, Databricks, Azure Synapse, or your existing lake or warehouse

Why choose Relevant for data ingestion services

Certified security and compliance

ISO 27001:2022 certified, GDPR covered, HIPAA-ready. Every landed record carries source lineage from the moment it arrives, so a compliance review has an answer instead of a guess.

The same engineers, start to finish

96% employee retention. The team that built your connectors is still there when a source changes its format a year later.

Customers who keep coming back

98% client satisfaction. Most ingestion engagements come from clients returning to add the next source.

AI-assisted, senior-reviewed

Our engineers use AI-assisted development to cut connector and CDC delivery time by up to 50% and reduce bugs by up to 20%, with every intake path still passing senior code review before production.

A roadmap before a build commitment

14 days to roadmap. You get a scoped intake plan and cost estimate before committing to the full build.

What clients say about Relevant

4.9 is our Clutch
average

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Frequently asked questions

How do you keep records from being dropped or duplicated when a source spikes or an ingestion job fails?

Our source has no API, only a database or a file export. Can you still ingest from it?

Can you take over ingestion pipelines another team or a vendor built?

How do you decide whether a source runs on batch, streaming, or change data capture?

What determines the cost and timeline of an ingestion build?

Which of your sources isn’t landing cleanly yet? Let’s scope the intake.

Why choose Relevant for data ingestion services

Certified security and compliance

ISO 27001:2022 certified, GDPR covered, HIPAA-ready. Every landed record carries source lineage from the moment it arrives, so a compliance review has an answer instead of a guess.

The same engineers, start to finish

96% employee retention. The team that built your connectors is still there when a source changes its format a year later.

Customers who keep coming back

98% client satisfaction. Most ingestion engagements come from clients returning to add the next source.

AI-assisted, senior-reviewed

A roadmap before a build commitment

14 days to roadmap. You get a scoped intake plan and cost estimate before committing to the full build.

Which of your sources isn’t landing cleanly yet? Let’s scope the intake.

Data ingestion services