The H1B database is the definitive repository of employer-sponsored visa petitions filed with U.S. Citizenship and Immigration Services. It functions by indexing approved Labor Condition Applications (LCAs) and corresponding visa petitions, allowing users to search by employer, job title, or fiscal year. This data provides a transparent record of historical hiring patterns and salary disclosures for H-1B beneficiaries. To use it, simply query the database by an employer name to view their petition count and offered wage levels.

What the H-1B Visa Registry Contains

The H-1B Visa Registry inside the h1b database contains the raw, case-level data that tells a worker’s story on record. You find the petitioner’s name—the sponsoring company—alongside the beneficiary’s name, job title, and the offered wage. Each entry shows the exact worksite address, the start and end dates of the visa period, and the labor condition application (LCA) case number. This is not a summary; it’s the granular fingerprint of every approved petition.

A single registry row might reveal a software engineer’s salary at a midtown Houston office, with a start date tied to a project kickoff, making the database a living log of who went where, for how much, and for what role.

Legal status changes, like an amendment or extension, also appear as separate entries, linking back to the original case. The registry strips away opinion and leaves only the hard facts of each visa’s administrative journey.

Understanding the Public Disclosure of Employer Petitions

Understanding the Public Disclosure of Employer Petitions reveals exactly which companies are actively seeking H-1B talent and for what roles. By exploring this subtopic within the broader H-1B database, you can see specific employer names, the job titles they petitioned for, the prevailing wage offered, and the petition’s final status—approved, denied, or withdrawn. This transparency lets you gauge an employer’s hiring intent and commitment to foreign workers without relying on rumors. For a quick comparison, the table below outlines key disclosure elements you can access:

Key Data Points: Wages, Locations, and Job Titles

The H-1B registry provides precise wage data tied to specific occupations, including prevailing annual salaries for each role. Job titles are detailed, ranging from entry-level to senior positions, enabling comparison of compensation across employers. Locations are recorded at the city and state level, allowing users to map salary ranges geographically. A logical sequence for analyzing this data involves:

1. Identify a specific job title and its corresponding wage level.
2. Cross-reference the wage with the intended work location.
3. Compare multiple employer entries for the same title and location to assess consistency.

These data points collectively reveal how wages vary by role and region within the registry.

How the Dataset Differs from Government FOIA Records

Unlike government FOIA records, which are often released in fragmented, redacted PDFs with inconsistent formatting, the H-1B dataset is typically compiled into a structured, searchable spreadsheet. This allows users to filter by employer, job title, or wage without sifting through individual case files. FOIA responses may also omit specific details like exact salary figures or beneficiary names due to privacy exemptions, whereas the curated H-1B dataset standardizes fields such as prevailing wage and worksite location across submissions. Additionally, FOIA requests can take months to fulfill and cover only the requested timeframe, while the dataset aggregates multiple years of data for immediate longitudinal analysis.

• Dataset includes uniform columns (e.g., case status, filing date); FOIA records often vary by request.
• FOIA redacts employer tax IDs and some salary ranges; the dataset preserves wage granularity.
• Government FOIA output may lack multi-year consistency; dataset merges certified petitions from 2019 onward.
• Dataset is downloadable as CSV/JSON for programmatic use; FOIA is typically delivered as PDF scans.

Navigating the Official Visa Records Online

The cursor blinks on the USCIS H1B database search portal, a gateway to decades of petition records. You type a company name, and results populate with case statuses, start dates, and wage levels. Navigating the Official Visa Records Online means parsing these raw entries—spotting denied petitions by red «Withdrawn» flags, tracking approval timelines, or verifying Labor Condition Applications against employer addresses. Each row is a thread connecting a foreign worker’s journey to a specific corporate filing. The real context is patience: filtering by fiscal year, cross-checking case IDs with public FOIA logs, and understanding that the data lags behind actual status. You bookmark a successful entry, knowing that official records hold the story no recruiter can tell.

Accessing the USCIS H-1B Employer Data Hub

To start exploring the official h1b database, head straight to the USCIS H-1B Employer Data Hub. You can download the raw CSV file or view it directly in your browser—no login required. The data updates quarterly, so check the “Last Updated” stamp before analyzing. Remember, the Hub only shows approved petitions, not total applications filed.

• Select a fiscal year from the dropdown menu to filter results.
• Use the “Search Employer” box to find a specific company’s records.
• Download the full dataset as a CSV for offline sorting and analysis.

Using the Department of Labor’s Disclosure Portal

The Department of Labor’s Disclosure Portal provides direct access to H-1B employer data, allowing you to query certified Labor Condition Applications. To use it, select the «LCA Disclosure Data» option, then filter by fiscal year and employer name. Each entry displays wage levels, worksite locations, and job titles. This portal is the definitive source for verifying wage compliance and employer volume. Querying the LCA database is the first logical step before cross-referencing USCIS petition approvals. Q: When should I use this portal? A: Use it after identifying a specific employer to confirm their certified job offers and offered wages for past fiscal years.

Search Tips for Finding Specific Filings

To refine your search in the H1B database, start by using the employer’s legal name exactly as registered with USCIS, as slight variations yield zero results. Apply date-range filters to isolate a specific fiscal quarter, which reduces noise from bulk filings. Use the exact case number when known for a direct hit. Wildcards often fail in structured databases, so spell out full company titles instead. What is the most reliable filter for narrowing a broad H1B search? Filtering by the certified status alongside a specific worksite city eliminates most rejected or pending applications.

Why Researchers and Analysts Rely on This Information

Researchers and analysts rely on the h1b database because it provides granular, historical data on actual employer filings and prevailing wage determinations. This raw information lets them trace hiring patterns for specific roles like software developers or analysts across different companies and geographies. By examining this data, they can independently verify salary trends for niche positions without relying on surveys. It also enables them to model labor market tightness and identify which firms dominate visa sponsorship for certain skill sets. Without this concrete record of past petitions and outcomes, analysts would lack a verifiable foundation to study employer behavior and wage distribution shifts within the skilled workforce.

Trending Salary Benchmarks Across Tech and Healthcare

Researchers and analysts mine the H1b database for trending salary benchmarks across tech and healthcare to set realistic compensation targets. They first isolate job titles like software engineer or physician, then compare base salaries across firms such as Google versus UnitedHealth to identify premium payers. The database reveals how location-adjusted wages shift year-over-year for identical roles. Analysts sequence this process:

1. Filter by occupation code and year to extract raw wage data.
2. Calculate median and percentile benchmarks for each job-title–location pair.
3. Cross-reference employer profiles to verify payment consistency.

These benchmarks inform negotiation floors and budget modeling for competitive hiring.

Geographic Distribution of Approved Petitions

The geographic distribution of approved petitions within the H-1B database reveals where skilled foreign talent is concentrated. Researchers rely on this data to map employer hubs and workforce density by state or metro area. For analysts, location-based petition trends identify which cities attract specific technical roles, such as software developers clustering in Seattle or Austin. A typical workflow for leveraging this geographic data includes:

1. Filtering approved petitions by employer city or zip code to isolate regional demand.
2. Cross-referencing petition volumes with local company headquarters to pinpoint primary hiring sites.
3. Comparing distribution across years to track shifts in talent relocation patterns.

This spatial breakdown directly supports site-selection analysis for expansion or workforce planning.

Detecting Shifts in Hiring Patterns Over Time

Researchers and analysts use the h1b database to track longitudinal hiring pattern shifts by comparing employer petition volumes across multiple years. They identify when a company abruptly increases or decreases its sponsorship of foreign talent for specific roles, such as software developers or data scientists. Cross-referencing yearly data reveals if a firm is relocating positions to new geographic hubs or phasing out certain job titles. This temporal analysis helps forecast which skillsets are falling from favor and which are emerging, enabling precise workforce planning rather than relying on static snapshots.

Legal and Privacy Boundaries of the Records

The Legal and Privacy Boundaries of the Records in an H1B database are defined by strict compliance with the Privacy Act and confidentiality obligations tied to USCIS Form I-129 filings. Accessing personally identifiable information—such as home addresses or beneficiary Social Security numbers—beyond the publicly posted labor condition application data is a direct violation. Practitioners must treat the database as a source for anonymized trend analysis only; downloading or repurposing individual records for marketing, background checks, or solicitation triggers legal liability.

The key insight is that the H1B database is not a public directory; treating it as such exposes you to data misuse claims, even if the data is scraped from government portals.

Any cross-referencing with external data sets to identify living individuals violates the intended boundary of record disclosure, which exists solely for program integrity verification, not employment research. Professional use demands rigorous filtering to expose only unique case identifiers and wage data.

What Information Is Redacted or Restricted

Within the H1B database, personally identifiable information (PII) is consistently redacted or restricted to comply with privacy laws. This includes home addresses, personal phone numbers, and email addresses of foreign workers, while employer business addresses remain visible. Social Security numbers and passport details are entirely withheld. Salary and wage data is often truncated or rounded to protect competitive compensation structures, and exact labor condition application (LCA) case numbers may be masked. Even job title descriptions can be partially redacted if they reveal sensitive proprietary technologies or internal organizational roles.

In summary, the H1B database redacts personal contact details, financial identifiers, and select employment specifics to balance transparency with individual privacy rights.

Compliance Rules for Employers Publishing Data

Employers publishing H-1B data must comply with strict redaction protocols to avoid exposing personally identifiable information (PII). Data minimization requirements mandate that only wage, job title, and work location fields are publicly displayed, while employee names, addresses, and Social Security numbers must be obscured. Cross-referencing wage data with internal HR systems is prohibited unless aggregate anonymization is verified. Audit logs of published records must remain accessible to demonstrate adherence to these boundaries. Any error in masking PII triggers an immediate takedown notice and retraction within 48 hours.

How Workers Can Verify Their Own Filing Details

Workers can verify their own filing details by first obtaining their unique case or receipt number from their employer’s legal team, then accessing the U.S. Citizenship and Immigration Services (USCIS) online case status tool. To ensure accuracy, they should cross-reference their name, job title, and start date with the certified Labor Condition Application (LCA) listed under their employer’s public disclosure records. A logical sequence for verification is:

1. Request a copy of your I-129 petition from your employer.
2. Log into the USCIS “Case Status Online” portal with your receipt number.
3. Compare your personal identifier details—such as passport number and date of birth—against the employer’s public LCA database entry.

This process confirms petition data integrity without violating employer confidentiality.

Tools and Platforms for Querying the Dataset

For the H1B database, effective querying relies on platforms that handle structured, record-level data. SQL-based tools like DBeaver or PostgreSQL are ideal for performing complex joins across wage, employer, and case status fields, enabling precise filtering by SOC code or fiscal year. For rapid exploratory analysis, DuckDB offers in-process OLAP querying directly on CSV or Parquet exports, handling millions of records without a server. Apache Superset provides a web-based SQL editor with visualization layers, allowing non-technical users to filter by employer name or job title.

A key insight: always index the employer name and case status columns before running aggregate queries—unindexed scans on the full dataset can take minutes due to its size.

Avoid Excel for raw queries; its row limits truncate the dataset.

Third-Party Sites That Aggregate Petition Information

For a quick snapshot of employer trends, third-party aggregation sites pull H1B data from public records and display it in easy-to-read charts. These platforms, like H1B Grader or MyVisaJobs, let you filter by employer name, job title, or salary range without digging through raw government files. You usually get a clean table showing approval rates, average wages, and petition counts per company. Some even offer side-by-side employer comparisons. Just remember these sites rely on previously published filings, so the data might lag behind the latest USCIS updates by a few months.

Building Custom Filters by Company or Occupation

To isolate specific trends within the H1B database, users can construct custom search filters by company name or occupational code. This allows you to bypass generic salary averages and pinpoint precise outcomes for a target employer like Amazon or a specific SOC category like Software Developers. By combining employer identity with occupation, you generate a hyper-focused dataset showing exact approval rates, prevailing wage levels, and case volumes for that niche. These filters transform raw government records into actionable intelligence for career planning or competitive research.

Building custom filters by company or occupation lets you drill down from broad data to precise, actionable insights on specific employers and job roles.

Exporting CSV Files for Deeper Analysis

For users needing more than surface-level insights, exporting CSV files for deeper analysis unlocks the full potential of the h1b database. By downloading raw data directly from query tools, you bypass platform limitations on visualization. This allows you to pivot, filter, and run statistical models in Excel, Python, or R, revealing correlations between employer size, wage percentiles, and petition status across years. A single exported CSV enables custom regression testing or trend-building that no dashboard can match. The table below contrasts export methods:

Common Misconceptions About the Public Repository

A prevalent misconception about the H1B database public repository is that it contains active, real-time visa statuses. In reality, the Department of Labor (DOL) data is historically static, reflecting only certified Labor Condition Applications (LCAs) from past filing cycles, not current adjudication outcomes. Another common error is assuming the repository lists all H-1B beneficiaries; it only tracks the employer’s job offer, not the applicant’s identity or final visa approval. Users often believe the data shows prevailing wage compliance, but it solely indicates the wage offered, not what was actually paid.

Treat the repository as a historical indicator of employer intent, not a verified employment or status tracker.

Understanding this prevents reliance on stale or incomplete records for compliance or background checks.

Distinguishing Between Approved and Active Cases

Many people think an approved H-1B petition in the database means the person is currently working in the U.S., but that’s not always true. An approved case only shows USCIS said yes to the application—the worker might still be abroad or haven’t started the job yet. An active case, however, means the visa holder is confirmed working. To tell them apart, check the status field in the record. Here’s a quick guide:

1. Look for approved status as a green light from USCIS, not a guarantee of active employment.
2. Find active case indicators like a start date and employer confirmation in the database.
3. Remember that approval can expire or be abandoned if the job never starts.

Why a Single Petition Does Not Guarantee a Visa Issuance

A single approved LCA petition in the H1B database does not guarantee visa issuance because it records only employer filings, not adjudication outcomes. Consular officers independently evaluate eligibility under specialty occupation criteria, including education equivalency and beneficiary qualifications. Even a certified petition can be denied if the officer finds inconsistent job duties or insufficient evidence. The H1B database simply reflects submitted labor condition applications; it omits denials due to administrative processing, quota exhaustion, or status violations. For users, this means a petition entry indicates only an employer’s request, not final approval. A clear sequence of steps shows why reliance on single records is misleading:

1. Petition certified by USCIS (database entry created).
2. Beneficiary undergoes consular review.
3. Officer verifies specialty occupation specifics.
4. Denial occurs if documentation fails scrutiny.

How Wage Discrepancies Appear in Different Sources

Wage discrepancies appear when comparing the H1B database’s certified Labor Condition Applications (LCAs) against actual reported wages. The database shows the prevailing wage determination used in the application, not the final salary. Employers may pay more or less than this figure. Additionally, LCAs list wages as annual salaries without prorating for part-time work, creating mismatches with payroll data. Different sources like company job postings or self-reported employee surveys reflect negotiated pay, which often diverges from the LCA’s standardized level.

• LCAs state the prevailing wage, while actual pay often varies by employer or negotiation.
• Part-time roles appear with full-time annual wages in the database, confusing comparisons.
• Job postings may advertise a range, whereas the LCA lists a single fixed wage.
• Employee salary databases rely on voluntary reports, not the certified LCA figures.

Using the Records for Job Market Intelligence

Using the H1B database for job market intelligence gives you a decisive edge in salary negotiations and employer targeting. By parsing certified LCA records, you identify exactly which companies pay the highest wages for your role in your city, then benchmark competing offers against actual approved wages. This data reveals if an employer consistently pays below market rate for your skill set. For example, Q: How can I spot a lowball offer? A: Cross-reference the employer’s prevailing wage for your job title against the median certified wage in the same Metropolitan Statistical Area; a significant gap signals exploitation. h1b database You also map hiring velocity—employers filing dozens of identical petitions are scaling rapidly, making them prime targets for direct applications.

Comparing Salaries by City and Industry

The H1B database enables precise salary comparison by city and industry by filtering employer-reported wage data against specific geographic and sectoral filters. Users can analyze how a software engineer role pays differently in San Francisco versus Austin, or compare tech industry compensation to healthcare within the same metropolitan area. This granular view reveals where skills command higher premiums, helping job seekers target cost-of-living-adjusted offers effectively.

• Cross-reference median wages for identical job titles across industries like finance vs. manufacturing in the same city.
• Identify cities where entry-level salaries for a given role exceed the national average for that sector.
• Compare senior-level pay disparities between major tech hubs and smaller urban centers.

Identifying Top Sponsors in Your Field

To start spotting the big players in your niche, just filter the H1B database by your job title and industry code. You’ll quickly see which companies file the most petitions and have the highest approval rates. Look for consistent repeat sponsors that hire multiple people for your role each year. These firms invest in visa pipelines, so they’re your real targets. Targing top H1B sponsors this way saves time because you skip companies that rarely sponsor. Also note their salary ranges—they reveal which employers value your skills most. Anchor your job search around these names for the best shot at sponsorship.

Predicting Application Windows Through Historical Trends

Analyzing historical H-1B data allows applicants to predict optimal filing windows by identifying recurring patterns in petition volumes and denial rates. By examining past fiscal years, one can pinpoint months with historically lower competition or higher approval likelihoods, such as early April surges versus later filing dips. The database reveals precise timing shifts for cap-subject petitions, enabling strategic submission planning. Comparing year-over-year receipt dates and processing delays further refines window predictions, helping users schedule around known administrative bottlenecks or seasonal employer filing clusters. This historical trend analysis directly informs when to prepare documentation and initiate applications for maximum efficiency.

What Exactly Is an H1B Database and How Does It Work?

Core Data Types Stored in a Typical H1B Database

How Wage Information and Employer Records Are Organized

Data Sources and Collection Methods Behind the Scenes

Key Features to Look for When Evaluating an H1B Data Tool

Search Filters That Save Time: Employer, Job Title, Location, and Year

Sorting and Exporting Options for Your Workflow

Real-Time vs. Historical Data: What Each Offers You

Practical Ways to Use This Resource for Job and Visa Planning

Identifying Employers Who Sponsor the Most Visas in Your Field

Comparing Prevailing Wages Against Actual Offered Salaries

Spotting Trends in Approval Rates by Company or Role

Tips for Getting the Most Accurate Results From Your Search

Using Wildcards and Advanced Search Syntax Effectively

Cross-Checking Data Between Multiple Records for Consistency

Understanding Common Data Gaps and How to Work Around Them

Common User Questions About Access and Reliability of These Databases

Is the Information Free to Search or Do You Need a Subscription?

How Often Is the Data Updated and How Fresh Is It?

Can You Trust the Wage Levels and Job Titles You Find?