AI visibility report
AI visibility report for Rivery in Data Engineering & ETL/ELT Pipelines.
Outside the top three on 21 of the 25 prompts buyers actually ask.
Integrate.io is cited on 13 of those losses.
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Start free trialStill absent from 91.2% of tracked prompt responses
Top-3 citations across 125 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Grok
Perplexity
Google AI Mode
ChatGPT
Gemini SearchHow to read this. Rivery appears in 8.8% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.
Where Rivery is losing
Prompts where competitors are visible and Rivery is not.
These prompt-level losses are the first prompts to track and repair.
Where Rivery is winning1
What ELT platforms handle schema drift and evolving source schemas automatically without breaking existing pipelines?
Avg # 3.0 · 1 platform
Where Rivery is losing5
What data pipeline tools integrate natively with major cloud data warehouses for automatic schema management and optimized load performance?
Competitors on 4 platforms
Track this promptWhich ELT platforms maintain low-latency incremental syncs so dashboards reflect source data within minutes rather than hours?
Competitors on 4 platforms
Track this promptWhat ETL platforms have built-in data quality checks and can alert the team when row counts or null rates deviate from expected ranges?
Competitors on 3 platforms
Track this promptWhich data pipeline platforms can a small data team of 2 get running with managed connectors for 20+ sources without building custom integrations?
Competitors on 3 platforms
Track this promptWhich data pipeline tools offer code-first transformation layers that data engineers can version-control and test like software?
Competitors on 3 platforms
Track this prompt
Track Rivery daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Rivery is a cloud-native, fully managed SaaS ELT platform founded in 2019 and headquartered in New York. The platform enables data teams to extract data from 200+ sources, load it into cloud data warehouses, and transform it using SQL or Python—all without managing infrastructure. Its proprietary 'Logic Rivers' orchestration layer allows users to build conditional, end-to-end data workflows combining ingestion, transformation, and reverse ETL in a single visual interface. Pre-built Starter Kits, CDC replication, and a GenAI-powered Data Connector Agent round out the product. Rivery targets data engineers, analysts, and data leaders at mid-market and enterprise companies. In December 2024, Boomi acquired Rivery for an estimated $100M, rebranding the product as Boomi Data Integration while maintaining core functionality and the rivery.io domain.
Rivery (now Boomi Data Integration) is a fully managed, cloud-native SaaS ELT platform that unifies data ingestion, SQL/Python transformation, workflow orchestration, CDC replication, and reverse ETL in a single no-code/low-code interface. Designed for data engineers, analysts, and data leaders, it eliminates infrastructure management while offering deep customizability through its Logic Rivers orchestration model, 200+ managed connectors, pre-built Starter Kits, and a GenAI-powered Data Connector Agent.
Key Facts
- Founded
- 2019
- HQ
- New York, USA
- Founders
- Itamar Ben Hemo, Aviv Noy, Alon Reznik +1 more
- Employees
- 51-100
- Funding
- $48M
- ARR
- ~$21M
- Customers
- 450+
- Valuation
- ~$100M (acquisition price, Dec 2024)
- Status
- Acquired (Boomi, Dec 2024)
Target users
Key Capabilities9
- Fully managed, serverless cloud ELT with 200+ native connectors
- Logic Rivers: modular, visual workflow orchestration with conditional logic, loops, and scheduling
- In-platform SQL and Python (DataFrame) transformations without additional infrastructure
- Change Data Capture (CDC) database replication to cloud warehouses
- Reverse ETL: sync warehouse data back into CRMs, marketing tools, and SaaS apps
- Pre-built Starter Kits and data model templates for rapid deployment
- DataOps management: multi-environment deployment, version rollback, RBAC, and pipeline monitoring
- GenAI-powered Data Connector Agent (Blueprint) for accelerated pipeline creation
- BDU credit-based consumption pricing with full visibility into usage
Key Use Cases7
- Centralizing marketing and advertising data from multiple platforms into a cloud warehouse
- Database replication and cloud migration via CDC
- Building end-to-end ELT pipelines for analytics and business intelligence reporting
- CRM data management and synchronization (Salesforce, HubSpot)
- Operational reverse ETL: enriching CRM or business tools with warehouse-derived insights
- AI and ML data pipeline preparation
- Cloud data lake ETL for consolidating disparate data sources
Rivery customer outcomes
VP of Analytics Ranajay Nandy reported that Rivery's pre-built Starter Kits enabled the team to build initial data pipelines rapidly and meet project objectives quickly out of the gate.
75% reduction in connector build time
Data Engineer Team Lead Romilly Hills reported that connector build time dropped from two weeks to half a day after adopting Rivery.
Recent Trend
How AI describes Rivery3
Fivetran, Airbyte, Matillion, Hevo Data, Rivery, and similar managed ELT/ETL platforms stand out for native or optimized integrations with major cloud data warehouses (Snowflake, Google BigQuery, Amazon Redshift, Databricks, etc.). These tools focus...
What data pipeline tools integrate natively with major cloud data warehouses for automatic schema management and optimized load performance?
Cloud-native/low-code (e.g., Azure Data Factory, Shipyard, Rivery): Visual drag-and-drop if you want even less code.
What data orchestration tools have the best getting-started experience for a data engineer moving from manually scheduled SQL scripts?
| | Rivery | ELT + orchestration | 1–4 hours | Useful when you expect workflows to grow.
What are the easiest ELT tools to get data flowing from a SaaS CRM into a cloud data warehouse in under a day with no custom code?
Most cited sources8
- 5
15 Best Data Orchestration Tools 2025 Compared | Rivery
rivery.io·Blog Post
- 3
Cloud ELT Tool | Data Pipeline & Integration Platform - Rivery
rivery.io·Listicle
- 2
What is Reverse ETL? Process & Use Cases
rivery.io·Listicle
- 1
Must-Have ELT tools for your Data Stack
rivery.io·Listicle
- 1
Data Ingestion Tool - Ingest any Data Source
rivery.io·Product Page
- 1
Big data statistics: How much data is there in the world?
rivery.io·Blog Post
Alternatives in Data Engineering & ETL/ELT Pipelines6
Rivery (now Boomi Data Integration post-December 2024 acquisition) differentiates as an all-in-one, fully managed, cloud-native SaaS ELT platform that unifies data ingestion, SQL/Python transformation, workflow orchestration, CDC replication, and reverse ETL inside a single product—eliminating the need to stitch together point solutions.
- Its proprietary 'Logic Rivers' orchestration model, no-code/low-code interface, and consistently top-rated support (G2 support score 9.4–9.8/10, highest in the ETL category) appeal to lean data teams that need enterprise-grade flexibility without infrastructure burden.
- Compared with Fivetran, Rivery offers deeper orchestration and in-platform transformations; compared with dbt Labs, it covers ingestion and orchestration as well; compared with Hightouch/Census, it extends further upstream.
- Its BDU credit-based pricing positions it as lower-cost than legacy ETL vendors but higher than open-source alternatives such as Airbyte or Meltano.
Reviews
Praised
- Flat learning curve and ease of use
- Industry-leading, engineering-led support responsiveness
- Fast connector and pipeline setup
- Logic Rivers orchestration for end-to-end workflows
- Pre-built Starter Kits accelerate time-to-value
- Automatic schema management and incremental loads
- Continuous product improvement and new feature cadence
- Proactive connector maintenance (e.g., API change notifications)
Criticized
- Pricing can escalate unpredictably with data volume growth
- CDC replication billed at 2x standard credit rate
- Python transformations restricted to higher-tier plans
- Smaller connector library compared to Fivetran
- Drag-and-drop rearrangement of complex nested Rivers is cumbersome
- Some documentation gaps require support escalation
- Boomi acquisition raises product roadmap and pricing trajectory uncertainty
- Not suitable for true real-time streaming workloads
Rivery earns consistently strong user reviews, anchored by a 4.7/5 rating on G2 across approximately 120 reviews and an industry-leading support score of 9.4–9.8/10—the highest in the ETL tools category on G2. Reviewers frequently praise the flat learning curve, responsive support team, fast connector setup, and the Logic Rivers orchestration model. G2 awarded Rivery top positions in 'Easiest to Use,' 'Best Support,' and 'Easiest to Do Business With' categories in multiple 2024 Grid Reports. Common criticisms include pricing that can escalate with data volume, fewer direct connectors than some competitors, and occasional complexity in managing nested pipeline workflows via drag-and-drop. Post-acquisition, some users have noted uncertainty about future roadmap and pricing trajectory under Boomi.
Pricing
Rivery uses a BDU (Boomi Data Unit, formerly RPU) credit-based consumption model. Pricing is calculated based on data volume (bytes processed) for database sources, or number of executions for API-based sources. Published rates cited by third-party sources include a Base/Starter tier at approximately $0.75–$0.90 per credit and a Professional tier at approximately $1.20 per credit. An Enterprise tier requires a custom sales quote. All plans include unlimited users, all 200+ connectors, unlimited SQL transformations, CDC, reverse ETL, and 24/7 support. Python transformations, high-frequency (5-minute) sync, SSO, and PrivateLink are restricted to Professional and Enterprise tiers. Following the Boomi acquisition, credits were rebranded from RPU to BDU; pricing structure remains largely consistent, but buyers should confirm current rates directly with Boomi.
Limitations
- Platform runs exclusively on AWS, limiting multi-cloud flexibility.
- CDC replication is billed at 2x standard credit rates, increasing costs for high-change-volume databases.
- Python transformations are restricted to Professional and Enterprise tiers.
- Minimum sync frequency on the Base plan is 60 minutes (5 minutes on higher tiers), making true real-time streaming unavailable.
- The BDU credit model can produce unpredictable costs as data volumes scale.
- The December 2024 acquisition by Boomi introduces product roadmap uncertainty—including potential connector consolidation, pricing changes, and whether the highly rated support team retains its identity.
- The connector library (200+) is smaller than Fivetran's (700+).
- Some users note drag-and-drop rearrangement of complex pipeline steps can be cumbersome.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Perplexity | ChatGPT | Gemini Search | Grok | Google AI Mode |
|---|---|---|---|---|---|
Capability4/5 cited (80%) | |||||
I need a reverse ETL tool to sync data warehouse segments back to a CRM and ad platforms — which platforms do this best? | |||||
What ETL platforms have built-in data quality checks and can alert the team when row counts or null rates deviate from expected ranges? | |||||
Which data pipeline tools support real-time streaming ingestion alongside batch loads from the same platform? | |||||
Which data orchestration tools support complex multi-step pipelines with branching logic, sensors, and cross-team dependencies? | |||||
What ELT platforms handle schema drift and evolving source schemas automatically without breaking existing pipelines? | |||||
Developer Experience0/5 cited (0%) | |||||
Which data pipeline tools have the best observability and data lineage views so you can trace where a bad value came from? | |||||
What ETL platforms do analytics engineers prefer when they want SQL-based transformations with testing and documentation built in? | |||||
Looking for a data orchestration platform with a great local development workflow — which tools let you test DAGs or workflows locally before deploying? | |||||
Which data pipeline tools offer code-first transformation layers that data engineers can version-control and test like software? | |||||
What ELT platforms give data engineers the best debugging experience when a pipeline fails mid-run with partial data loaded? | |||||
Integrations & Ecosystem1/5 cited (20%) | |||||
What data pipeline tools integrate natively with major cloud data warehouses for automatic schema management and optimized load performance? | |||||
Which ETL tools have an open API and SDK so we can build custom connectors for internal data sources quickly? | |||||
Looking for an orchestration platform that integrates with my existing transformation layer — which tools support running SQL models as pipeline steps? | |||||
Which ELT platforms have the largest library of pre-built source connectors covering SaaS apps, databases, and event streams? | |||||
What data engineering platforms work well in a multi-cloud setup where sources span one cloud and the warehouse is on another? | |||||
Performance & Reliability2/5 cited (40%) | |||||
Which ELT platforms can sync billions of rows per day from a high-volume transactional database without impacting source system performance? | |||||
What data pipeline tools handle late-arriving data and backfilling years of historical records reliably without manual intervention? | |||||
What data orchestration tools scale reliably to thousands of concurrent tasks without degrading scheduler performance? | |||||
Which ETL platforms have strong SLAs and automatic retry logic so data teams get alerted before business stakeholders notice pipeline delays? | |||||
Which ELT platforms maintain low-latency incremental syncs so dashboards reflect source data within minutes rather than hours? | |||||
Setup & First Run2/5 cited (40%) | |||||
Which data pipeline platforms can a small data team of 2 get running with managed connectors for 20+ sources without building custom integrations? | |||||
What are the easiest ELT tools to get data flowing from a SaaS CRM into a cloud data warehouse in under a day with no custom code? | |||||
I'm evaluating ETL platforms for a company starting its modern data stack — which tools are fastest to onboard and connect to a cloud warehouse? | |||||
What data orchestration tools have the best getting-started experience for a data engineer moving from manually scheduled SQL scripts? | |||||
Which open-source ETL tools can be self-hosted on a single VM and are easy to configure without deep infrastructure knowledge? | |||||
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Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | Integrate.io | 43.2% | 19.7% | 0.0% | 42.4% | 36.8% | #22.6 | +0.24 |
| 2 | Fivetran | 32.8% | 22.2% | 13.6% | 16.0% | 31.2% | #29.0 | +0.23 |
| 3 | Airbyte | 27.2% | 15.9% | 8.0% | 2.4% | 24.8% | #23.4 | +0.27 |
| 4 | Hevo Data | 22.4% | 5.1% | 1.6% | 1.6% | 16.0% | #22.9 | +0.28 |
| 5 | Dagster Labs | 21.6% | 11.9% | 4.8% | 8.0% | 13.6% | #28.4 | +0.24 |
| 6 | dbt Labs | 20.0% | 7.9% | 2.4% | 14.4% | 16.0% | #21.2 | +0.20 |
| 7 | Matillion | 18.4% | 6.3% | 3.2% | 0.0% | 16.8% | #27.4 | +0.20 |
| 8 | Rivery | 8.8% | 1.6% | 0.0% | 2.4% | 8.0% | #15.2 | +0.24 |
| 9 | Astronomer | 8.8% | 2.5% | 5.6% | 1.6% | 6.4% | #37.2 | +0.13 |
| 10 | Meltano | 5.6% | 4.7% | 3.2% | 3.2% | 5.6% | #30.5 | +0.29 |
| 11 | Hightouch | 3.2% | 1.9% | 0.8% | 3.2% | 3.2% | #29.2 | +0.38 |
| 12 | Census | 0.8% | 0.1% | 0.0% | 0.0% | 0.8% | #41.0 | +0.80 |
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