ETL & Database Providers

Unstructured data pipelines for ETLs and database providers

Datastreamer is used by engineering teams to ingest and enrich unstructured data sources into databases.

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Structured Streams

Built for converting unstructured
data into structured streams

Datastreamer enables database and indexing platforms to ingest and process unstructured data efficiently, transforming it into structured formats ready for indexing and retrieval. This integration enhances search functionalities and data accessibility for end-users.

Platform Support

How Datastreamer supports database
and indexing platforms

Unstructured data transformation
Converts unstructured data into structured formats compatible with your indexing systems.
Metadata enrichment
Add valuable metadata, such as timestamps, geolocation, vectoring, and topic tags, to enhance search relevance.
Real-time and flexible
Deliver processed data to your database, ETL, or indexing platforms via APIs, webhooks, or direct database connections.
Maintenance-free pipelines
Reduce operational overhead with managed pipelines that require minimal maintenance.
Use Cases

Built for teams that need more
than scrapers and scripts

Ready-to-use components allow complex multi-source data pipelines to be assembled in minutes. Deployment happens instantly and is fully managed, allowing low-latency, high volume processing.

Social → Datalakes
Continuous data collection and structuring of varied social data sources, melded to existing schemas.
Files → JSON
Structuring of scanned PDFs and other files into enriched JSON, accelerating due diligence.
Streams → Storage
Handling streaming real-time data sources by batching in pipelines and sorting to lower input rates.
Proserv → Automation
Reducing custom integration work using pre-built library of connectors.
AI Application → Searchability
Applying vectors, LLM prompts to the data pre-ingestion to increase search performance and volume.
Storage-free → Processing
With storage-free processing by default, meet adherence to compliance and sub-processing requirements.
By the Numbers

Why product and engineering
teams use Datastreamer

6 weeks
reduced build time per new source or enrichment connection
$285k
average annual benefit per Datastreamer customer
6,373
average annual people hours of pipeline work saved
80M
average pieces of web content consumed monthly per pipeline
7+
average datasources or enrichments used per pipeline
38,000+
ready-to-deploy capabilities available in the Datastreamer registry
Data Pipelines for Database Platforms

Questions from engineering teams

Using Datastreamer, your engineering teams can rapidly deliver the data pipelines for complex use cases, reducing speed-to-launch of new features by 85%.

What types of datasources are supported?
Anything from social platforms, review sites, forums, other SI platforms, SERP data, trend tools, or any other inputs. Datastreamer handles structured and unstructured inputs. With over 38,000 ready-to-use capabilities, it's very easy to meet every ask.
Can I apply custom enrichment or taxonomies?
Yes. Datastreamer has a full registry of ready-to-use NLP models. You can also use LLMs in pipelines or plug in your own logic and systems through APIs.
How do you handle schema consistency across sources?
We abstract each source into a common schema, so your downstream systems don't have to handle structural drift, missing fields, or format mismatches.
How can Datastreamer help support compliance requirements?
While compliance requirements can be quite broad and use-case specific, Datastreamer has a wealth of data processing, PII detection, redaction, hashing, and other capabilities that you can use in your pipelines.
What makes Datastreamer better than building it in-house?
Faster time to market, no ongoing maintenance, and a much lower risk surface for managing content ingestion and normalization.
Is Datastreamer self-hosted or managed?
It's fully managed. There is no infrastructure to deploy or maintain. We handle scaling, updates, and availability so your team can stay focused on building product.
Does Datastreamer partner with any providers?
Yes, we partner with many providers for ETL, database, and similar offerings. ElasticSearch, Google Cloud, Fivetran, and more are listed partners of Datastreamer.
Get Started

Ready to build your data pipelines?

Datastreamer is the social and web data orchestration platform loved by intelligence software companies. Talk to our team about ingesting and enriching unstructured data into your database, ETL, or indexing platform.

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Fully managed pipelines. No infrastructure to deploy or maintain.