A novel approach that bridges relational databases with blockchain technology, providing unprecedented data integrity and verification while maintaining enterprise-level performance.
Relational databases lack intrinsic cryptographic verification. Blockchain systems offer poor query capabilities.
BlockchainSQL bridges this gap. It combines SQL query capabilities with blockchain immutability.
Based on patented Slidechain technology. Enables multi-branched blockchain architecture for optimal scaling.
Standard SQL with blockchain extensions
Optimizes queries across current and historical states
Implements multi-branched Slidechain architecture
Handles cryptographic proof generation and validation
Each database table assigned to its own branch
Secondary indexes maintain separate blockchain branches
Schema definitions and metadata in dedicated branches
Cryptographic links ensure global consistency
Traditional SQL syntax for current state queries.
SELECT * FROM sensor_readings
WHERE temperature > 30.0;Access historical database states at specific block heights.
SELECT * FROM medical_records
AS OF BLOCK 12345
WHERE patient_id = 'P789';Generate cryptographic proofs with query results.
SELECT * FROM document_registry
WITH VERIFICATION
WHERE document_hash = 'f58920a...';All changes applied completely or not at all.
Preserves database integrity and blockchain validity.
Concurrent transactions cannot see uncommitted changes.
Committed transactions recorded permanently.
Each transaction produces cryptographic proofs.
Committed transactions cannot be altered.
Efficiently persists immutable blocks with compression and cryptographic linking.
Maintains working copies of current state for efficient reads and updates.
Coordinates across multiple blockchain branches for optimal scaling.
Creates complete state snapshots to facilitate historical queries.
Cryptographic hashes link blocks to predecessors
Efficient verification of data within blocks
Links between related blocks in different branches
Publication of hashes to external systems
Proves existence and value of specific records.
Proves completeness of results for range queries.
Proves specific records do not exist.
Proves record state at specific points in time.
Maintains multiple data versions for optimal isolation.
Ensures consistent state transitions across branches.
Policies determine which transactions proceed during contention.
Non-conflicting operations on different branches proceed independently.
Performance benchmarks show BlockchainSQL achieves 85-90% of traditional RDBMS query performance while providing blockchain verification benefits.
For real-time IoT data vs. single-branch systems
On aggregated data branches
Through branch-specific retention policies
Maintained across branch boundaries
Cross-branch verification queries complete in 75-120ms for typical data volumes.
Verification proof generation adds only 15-25% overhead to queries.
Cached verification paths reduce subsequent verification time by 85%.
Verification proof size remains compact (2-5KB) even for complex queries.
# Connect to a BlockchainSQL database
from blockchainsql import BlockchainDB
# Connect with standard credentials
db = BlockchainDB(host="db.example.com",
port=5432,
username="app_user",
password="secure_pass")
# Execute a verification-enabled query
result = db.execute_query("""
SELECT * FROM iot_sensor_data
WITH VERIFICATION
WHERE device_id = %s
AND reading_time > %s
""", ["DEVICE-001", "2025-01-01T00:00:00Z"])
# Verify the proof
if result.verify_proof():
print("Data verified successfully")
import { BlockchainSQLClient, VerificationLevel }
from 'blockchainsql';
// Initialize client
const client = new BlockchainSQLClient({
host: 'db.example.com',
port: 5432,
user: 'app_user',
password: 'secure_pass',
database: 'product_registry'
});
// Query with verification
const result = await client.query({
sql: `SELECT current.description AS current_description,
historical.description AS original_description,
current.last_modified_block - historical.last_modified_block
AS blocks_since_change
FROM products current
JOIN products AS OF BRANCH_ROOT historical
ON current.product_id = historical.product_id
WHERE current.product_id = $1
AND current.description <> historical.description`,
params: [productId],
verificationLevel: VerificationLevel.MERKLE_PROOF
});
import com.blockchainsql.BlockchainSQLConnection;
import com.blockchainsql.VerificationOptions;
// Establish connection to BlockchainSQL
try (BlockchainSQLConnection conn =
BlockchainSQLConnection.builder()
.withHost("db.example.com")
.withPort(5432)
.withCredentials("app_user", "secure_pass")
.withDatabase("supply_chain")
.build()) {
// Query with verification
VerifiedResultSet results = conn
.prepareVerifiedStatement(
"SELECT inventory.product_id, " +
"inventory.quantity, " +
"certifications.certification_id, " +
"certifications.expiration_date " +
"FROM BRANCH('inventory') inventory " +
"JOIN BRANCH('certifications') certifications " +
"ON inventory.product_id = certifications.product_id " +
"WHERE inventory.warehouse_id = ? AND " +
"certifications.is_valid = true"
)
.setString(1, "WAREHOUSE-A")
.withVerificationOptions(new VerificationOptions()
.includeBlockHeaders(true)
.includeMerkleProofs(true)
.signResult(true))
.executeQuery();
}





BlockchainSQL provides comprehensive SDK support across multiple programming languages, including Rust, C, C++, Python, and JavaScript/TypeScript.
from blockchainsql.lineage import LineageTracker
# Initialize lineage tracker
tracker = LineageTracker(db_connection)
# Track complete history of a data point
lineage = tracker.trace_lineage(
data_id="PATIENT-1234-BLOODWORK-2025-04-01",
include_branches=True,
include_metadata=True
)
# Visualize the lineage graph
lineage.export_graph("patient_data_lineage.svg")
# Verify integrity of entire lineage chain
verification_result = lineage.verify_complete_chain()
if verification_result.is_valid:
print("Complete data lineage verified successfully")
else:
print(f"Lineage verification failed: {verification_result.failure_reason}")
import { SchemaManager } from 'blockchainsql-schema';
// Initialize the schema manager
const schemaManager = new SchemaManager({
connection: dbClient,
schemaName: 'medical_records'
});
// Create a versioned schema change
const migrationPlan = await schemaManager.createMigration({
name: 'add_patient_consent_fields',
changes: [
{
type: 'ADD_COLUMN',
table: 'patient_records',
column: {
name: 'consent_date',
dataType: 'TIMESTAMP',
nullable: false,
defaultValue: 'NOW()'
}
},
{
type: 'ADD_COLUMN',
table: 'patient_records',
column: {
name: 'consent_version',
dataType: 'VARCHAR(50)',
nullable: false,
defaultValue: "'v1.0'"
}
}
]
});
import com.blockchainsql.compliance.ComplianceReporter;
import com.blockchainsql.compliance.ReportFormat;
import com.blockchainsql.compliance.ReportCriteria;
// Initialize compliance reporting engine
ComplianceReporter reporter = new ComplianceReporter(connection);
// Generate GDPR compliance report with verification
ReportResult gdprReport = reporter.generateReport(
new ReportCriteria()
.withReportType("GDPR_DATA_ACCESS")
.withSubjectIdentifier("citizen-id-12345")
.withTimeRange(startDate, endDate)
.withVerificationLevel(VerificationLevel.FULL)
.withFormat(ReportFormat.PDF)
);
// Export the verified report
File reportFile = gdprReport.exportToFile("gdpr_compliance_report.pdf");
String verificationUrl = gdprReport.getVerificationUrl();
Pull data from legacy sources with verification checkpoints.
Apply transformations while maintaining verification trails.
Insert into BlockchainSQL with complete data provenance.
Generate proof of complete ETL process integrity.
import { BlockchainSQLEventProcessor } from 'blockchainsql-events';
// Create event processor for real-time data
const eventProcessor = new BlockchainSQLEventProcessor({
connection: dbClient,
sourceTable: 'iot_sensor_readings',
processingOptions: {
verifyBeforeProcessing: true,
recordProcessingEvents: true,
enableRollback: true
}
});
// Register event handlers
eventProcessor.onData(async (reading) => {
// Process each sensor reading
if (reading.temperature > temperatureThreshold ||
reading.humidity > humidityThreshold) {
// Create alert with verification link
await alertSystem.createAlert({
deviceId: reading.device_id,
alertType: 'THRESHOLD_EXCEEDED',
readingValues: {
temperature: reading.temperature,
humidity: reading.humidity
},
verificationData: {
blockchainRef: reading._blockchainRef,
blockHeight: reading._blockHeight
}
});
}
});
// Start real-time processing
eventProcessor.start();
Cryptographically hash model architecture and initial weights.
Record hashes of training datasets without exposing sensitive data.
Track all model changes with immutable blockchain records.
Ensure deployed model matches verified version.
Record inputs and outputs for critical AI decisions.
Opaque AI creates a black hole in democratic governance. Citizens cannot understand decisions.
Governments must explain decisions in court. Black-box AI makes this impossible.
AI trained on biased data may embed discriminatory logic without detection.
Opaque models are harder to secure against adversarial attacks.
Unexplainable decisions erode public trust in government legitimacy.
Laws like EU AI Act require explainability. Black-box AI creates liability.
Record and verify regulatory decisions with complete audit history.
Maintain verifiable identity records with strong privacy controls.
Ensure transparency and immutability in government contracting.
Record verifiable AI model states used in government decisions.
Verifiable financial records with sophisticated query capabilities.
Generate verifiable reports for regulatory submissions.
Analyze transaction patterns while maintaining evidence integrity.
Manage digital assets with verifiable provenance tracking.
BlockchainSQL bridges the gap between traditional databases and blockchain, offering unprecedented data integrity with near-traditional performance levels.
BlockchainSQL: Revolutionizing Database Paradigms