ReJot

What do they actually do

ReJot builds a database-to-database sync engine that lets engineering teams share internal data asynchronously without adding new synchronous APIs. It reads database changelogs/WAL to publish versioned "public" schemas and lets consuming teams define their own "consumer" schemas to replicate data into their own databases, with SQL-based transformations and contracts owned in code docs home. The control plane doubles as a searchable data catalog of connected data stores, so teams can see what’s available before wiring up a sync YC launch.

Deployments can run hybrid or self‑hosted so sensitive data stays inside the company network home. The team is rolling out an open‑source limited access preview while they onboard early users YC launch.

Who are their target customer(s)

• Product engineering teams needing data from other internal services: They wait on API/schema changes, couple to another team’s runtime, and lose weeks coordinating interfaces. They want to query or replicate published data directly into their own DB instead of chaining service calls.
• Internal platform/data-infrastructure teams operating integration layers: They carry the burden of running Kafka/connectors and building one‑off pipelines. They want a lighter path that uses DB changelogs for async sharing and reduces operational overhead.
• Analytics/data engineering teams seeking trustworthy internal datasets: They spend time discovering what exists and chasing ad‑hoc exports that don’t match needs. They want discoverable, versioned internal datasets with transformation hooks to land data in a usable shape.
• Security/compliance/platform‑ops teams managing data governance: They need clear contracts on what’s shared and to avoid routing internal data through third‑party services. They prefer hybrid/self‑hosted options and explicit data‑sharing controls.
• Reliability/SRE teams mitigating cascading failures from sync dependencies: They see incidents from chained service calls and want services to remain available when others fail. They prefer asynchronous, database‑based replication to decouple services.

How would they acquire their first 10, 50, and 100 customers

• First 10: Use YC/founder networks to run hands‑on pilots with teams that own a source DB and downstream consumers; ReJot engineers handle install of the self‑hosted agent and replicate one published dataset end‑to‑end so the team can evaluate without third‑party routing YC launch docs.
• First 50: Turn pilots into repeatable offers with 1‑page POC playbooks, connector templates for common stacks, and 2 case studies; open a small sales‑engineering funnel (outbound to platform/data teams + dev community outreach) and run targeted workshops to convert pilots to paid deployments.
• First 100: List in cloud marketplaces, add SI/consultancy partnerships with implementation packages, and standardize onboarding with a small CS team; let SEs focus on larger accounts while marketing runs technical content and account‑based campaigns for target industries.

What is the rough total addressable market

Top-down context:

ReJot sits inside the data integration/data replication segment. Estimates peg the data integration and integrity software market around $14.8B in 2024 and $16.6B in 2025, growing ~12% CAGR to ~$36B by 2032 Fortune Business Insights. Grand View Research similarly sizes the broader data integration market at ~$15.2B in 2024 and ~$17.1B in 2025, ~12% CAGR through 2030 Grand View Research.

Bottom-up calculation:

Near term, focus on mid‑to‑large enterprises with multiple service teams and strict data controls. If 8,000–12,000 global enterprises fit this profile and 10–15% are in‑market over 3–5 years (800–1,800 buyers) at a blended ACV of $75k–$150k for hybrid/self‑host plus support, the initial serviceable opportunity is roughly $60M–$270M annually, with room to expand toward $1B+ as adoption widens across more teams and regions.

Assumptions:

• Targetable enterprises are those with multi‑team service architectures and governed data (subset of 1,000+ employee firms).
• Adoption ramp assumes 10–15% in‑market over 3–5 years given procurement/security cycles.
• Blended ACV includes licensing/support for hybrid/self‑hosted deployments and limited connectors.

Who are some of their notable competitors

• Debezium: Open‑source CDC that reads DB changelogs and emits row‑level changes, typically into Kafka. Overlap on CDC; differs because you operate Kafka/Connect and assemble the rest of the pipeline yourself, whereas ReJot packages capture with a consumer‑facing sync/catalog layer Debezium ReJot docs.
• Airbyte: Connector platform for moving data between systems (many prebuilt sources/destinations). Overlap on table/CDC replication; differs by focusing on generic movement into warehouses/DBs and leaving contracts/discoverability to users, while ReJot emphasizes team‑owned published schemas and lightweight team‑to‑team sharing Airbyte ReJot.
• Confluent / Kafka Connect: Enterprise Kafka plus a connector framework to move data in/out of Kafka. Overlap via streaming DB changes across teams; differs as Kafka ecosystems are infra‑heavy (clusters, topics, schema registry) vs. ReJot’s database‑to‑database replication with explicit contracts Confluent docs ReJot.
• Fivetran: Managed CDC for keeping destinations/warehouses in sync. Overlap on reliable CDC; differs by focusing on analytics ingestion with a managed cloud model, while ReJot targets engineering‑to‑engineering sharing with on‑prem/hybrid options and explicit publish/consume contracts Fivetran ReJot docs.
• Hightouch (reverse ETL): Syncs data from a central warehouse into operational tools. Overlap in getting ready‑to‑use data into downstream systems; differs because Hightouch assumes a warehouse as source, whereas ReJot shares owner‑published operational datasets directly between engineering teams with versioned schemas and self‑host options Hightouch ReJot.