A Data Stream is the end-to-end flow your data takes from sources through processing to your destination. Datastreamer manages every stage: ingestion, enrichment, transformation, and delivery.
Datastreamer orchestrates the full journey. You configure what you want. The platform handles the rest.
Auto sources bring full provider and source flexibility to your Data Streams and pipelines. Datastreamer curates a network of data source providers, so that Auto routes your query to the best provider for its requirements.
Auto provides resiliency, scalability, and consistency by handling the routing and selection, and Unify then transforms the results into a standard schema for streamlined usage downstream.
Both paths use the same processing and pipeline infrastructure. The difference is how data sources are managed.
Building and maintaining data connectors is undifferentiated work. Datastreamer was designed to take that off your engineering team's plate permanently.
Building your own social data pipeline platform means owning every layer: connector maintenance, infrastructure ops, AI model management, and everything in between.
| Capability | Build In-House | Datastreamer |
|---|---|---|
| Social & web data connectors | 6 to 18 months of engineering per connector set. Ongoing auth & API maintenance. Breaks every time a platform changes. | Hundreds of pre-built, production-grade connectors. Maintained by Datastreamer's ops team. New sources added regularly. |
| AI & NLP enrichments | Model research, training, and deployment per enrichment. Requires ML infrastructure and specialized expertise. | 30+ ready-to-use AI operations: sentiment, NER, language, brand recognition, ESG, emotion, intent & more. |
| Unified output schema | Custom normalization code per source. Schema drift and inconsistency as sources change. Hard to query across sources. | 493-field unified schema across all connectors. Consistent structure regardless of source. Always queryable together. |
| Audio & video analysis | Separate transcription pipeline, custom integration, storage requirements, manual orchestration. | Social Voice handles transcription, translation, tonality, toxicity, entities, and IAB categories in-pipeline with no extra infrastructure. |
| Auto-scaling infrastructure | DevOps team required to provision, monitor, and scale. Over-provisioning is expensive; under-provisioning breaks SLAs. | Fully managed auto-scaling within seconds. Usage-based billing means you pay for exactly what you consume. |
| Pipeline observability & debugging | Custom logging, metrics dashboards, alerting, and on-call rotation for pipeline failures. | Built-in pipeline analytics, failed items viewer, document inspector, component logs, and volume health alerting. |
| Compliance & PII controls | Legal review per data source, custom redaction logic, compliance-mode ETL handling. Ongoing legal and engineering cost with no clear end state. | Regional deployment, compliance-sensitive connector modes, and Private AI PII redaction, all configurable per pipeline. |
| Cost management | Unpredictable infrastructure costs. Separate tooling for budget tracking. No per-job cost visibility. | DVU-based usage pricing, per-job cost visibility, budget alerts, tag-level billing, committed discount tiers. |
Talk to our team. We'll help you design the right configuration for your use case and get you running with the sources you need, fast.
Used by market-leading intelligence platforms. Supported by a dedicated success team.