Apache Spark Connectivity Architecture

Connect your business applications to Apache Spark using SQL

Business Applications & Tools

📊
Microsoft Office
Excel, Access, PowerPoint integration
🗄️
SQL Server
Database queries and stored procedures
💎
Crystal Reports, Power BI, Tableau
📊
BI Tools
Analytics and dashboard platforms
⚙️
Custom Apps
Bespoke business applications
🔄
ETL Tools
Data integration and migration
SQL Statements
🔗

Apache Spark ODBC Driver

High-performance SQL interface for Apache Spark data

🚀 Performance

Optimized queries with intelligent caching and connection pooling

🔒 Security

SSL encryption

🔄 Real-time

Live data synchronization with automatic change detection

📊 SQL Support

Full SELECT, INSERT, UPDATE, DELETE operations

Technical Specifications

Supported Operations: Full CRUD operations (Create, Read, Update, Delete) with transaction support

Performance: Connection pooling, query optimization, and result set caching for maximum throughput

Authentication: User/Password.

Platforms: Windows, Linux and UNIX with 32-bit and 64-bit support

Standards: ODBC 3.8 compliant

Apache Spark Protocol
Apache Spark
"Lightning-fast unified analytics engine for large-scale data processing"
⚡
Spark Core
Distributed computing engine with RDDs, fault tolerance, and memory management
📊
Spark SQL
Structured data processing with DataFrames, Datasets, and SQL interface
🧠
MLlib
Scalable machine learning library with algorithms and utilities
🌊
Spark Streaming
Real-time stream processing and micro-batch computation
🕸️
GraphX
Graph processing and analytics with distributed graph algorithms
🏗️
Cluster Manager
Support for YARN, Mesos, Kubernetes, and standalone cluster modes

🎯 Use Cases

Reporting & Analytics

Create dashboards, reports, and KPI tracking using familiar SQL tools

Data Integration

Sync Apache Spark data with ERP, accounting, and other business systems

Business Intelligence

Connect BI tools for advanced analytics and data visualization

Data Migration

Import/export data from legacy systems and databases

⚙️ Configuration & Setup

Easy Configuration: Standard ODBC Data Source Administrator or connection string setup.

  • Apache Spark User/Password
  • Query optimization parameters

Step-by-Step Setup

1. Installation: Download and install the Apache Spark ODBC driver package

2. Configuration: Use ODBC Administrator to create a new data source

3. Connection: Enter Apache Spark server details and user/password

4. Testing: Test connection and verify data access permissions

5. Usage: Connect from your applications using the configured DSN

🔧 Features & Benefits

  • Standard SQL syntax for familiar development
  • Real-time data access with automatic refresh
  • Support for custom fields and modules
  • Enterprise-grade security and encryption
  • Comprehensive logging and debugging tools
  • Technical support and documentation

📊 Supported Data Operations

Read Operations: Query leads, contacts, accounts, opportunities, and custom objects

Write Operations: Insert new records, update existing data, and delete obsolete entries

Advanced Features:

  • Complex JOIN operations across modules
  • Aggregate functions (COUNT, SUM, AVG, etc.)
  • Filtering and sorting with SQL WHERE clauses
  • Transaction support for data consistency