Ververica Platform

Enterprise Flink. For Those Who Cannot Get It Wrong.

We built Flink
We know where it breaks.
We fixed it

2x: Throughput
40%: Lower TCO
100%: Flink API compatible

Auto-scaling. Auto-recovery. SOC 2 certified. Zero-downtime upgrades. Multi tenant governance. Plus 2x throughput and 40% lower TCO. 100% Flink API compatible. Drop-in replacement.

What Is Ververica Platform?

The enterprise streaming and batch platform built by the original creators of Apache Flink. Unified stream and batch processing in one runtime. Materialized tables that maintain themselves. Auto-scaling, auto-recovery, SOC 2 & ISO 27001 certified, zero-downtime upgrades, multi-tenant RBAC everything production Flink needs, built in. Not bolted on.

Key Statistics

0x: Faster ProcessingThroughput vs open-source Flink
0%: Lower TCOSame workload, less infrastructure
0%: Flink CompatibleZero migration effort required
<0s: RecoveryAutomatic checkpoint restore

The Problem

Open-Source Flink Is Powerful. Production Is the Hard Part. Manual cluster sizing. No auto-scaling. 2-5 minute recovery times on failure. Upgrades require downtime. No RBAC. No compliance certifications.

Technology Innovations

Why Ververica

Unified Stream & Batch

Traditional: Spark batch + Flink stream, 2x cost
Ververica: One SQL both modes, freshness-driven execution, 40-60% Less Cost

State & Recovery

OSS: 2-5 min recovery, full checkpoint
Ververica: <30s auto-recovery, 60% smaller checkpoints

Zero Migration

Typical: Rewrite code, months to validate.
Ververica: Same SQL & DataStream, deploy done. 0 Code Changes.

Vectorized Execution

OSS: Row-by-row, full CPU burn
Ververica: Columnar SIMD batches, 40% less CPU, 2x Throughput

Benchmarks Table

Feature	Ververica	Open-Source	Improvement
Throughput	6.9B records/sec	3.4B records/sec	2x
Latency (p99)	8ms	45ms	5.6x
Resource Usage	60%	100%	40% less
Recovery Time	< 30 seconds	2-5 minutes	10x
Checkpoint Duration	1.2 seconds	3.1 seconds	2.6x

Unified Processing

One Platform. Streaming and Batch. Unified.

Unified Semantics

Freshness-Driven Execution

Built-In Scheduling

Resource Isolation

10x Faster Deployment

40-60% Cost Reduction

97% Faster Snapshots

Materialized Tables

Define Once. Always Fresh. Query Instantly

Interactive MaterializedTableDemo component

SQL-Native

Always Fresh

Instant Lookups (<10ms)

Compatibility (Zero Migration)

Your Flink Code. Unchanged.

Flink SQL syntax

DataStream API

Table API

All connectors

State backends

Checkpointing

Savepoints

Python UDFs

Custom serializers

Metrics reporters

Enterprise Flink. Production Ready.

Auto-scaling, auto-recovery, SOC 2 certified. Same Flink code, 2x throughput, 40% lower TCO.

Start free trial Book a demo