Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • DataBuck Reviews & Ratings
    6 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    2,027 Ratings
    Company Website
  • Runpod Reviews & Ratings
    230 Ratings
    Company Website
  • Servers.com by Nexcess Reviews & Ratings
    15 Ratings
    Company Website
  • AnalyticsCreator Reviews & Ratings
    46 Ratings
    Company Website
  • Chainstack Reviews & Ratings
    35 Ratings
    Company Website
  • Dragonfly Reviews & Ratings
    16 Ratings
    Company Website
  • Ganttic Reviews & Ratings
    242 Ratings
    Company Website
  • Google Cloud Platform Reviews & Ratings
    61,066 Ratings
    Company Website
  • Float Reviews & Ratings
    3,787 Ratings
    Company Website

What is Google Cloud Dataflow?

A data processing solution that combines both streaming and batch functionalities in a serverless, cost-effective manner is now available. This service provides comprehensive management for data operations, facilitating smooth automation in the setup and management of necessary resources. With the ability to scale horizontally, the system can adapt worker resources in real time, boosting overall efficiency. The advancement of this technology is largely supported by the contributions of the open-source community, especially through the Apache Beam SDK, which ensures reliable processing with exactly-once guarantees. Dataflow significantly speeds up the creation of streaming data pipelines, greatly decreasing latency associated with data handling. By embracing a serverless architecture, development teams can concentrate more on coding rather than navigating the complexities involved in server cluster management, which alleviates the typical operational challenges faced in data engineering. This automatic resource management not only helps in reducing latency but also enhances resource utilization, allowing teams to maximize their operational effectiveness. In addition, the framework fosters an environment conducive to collaboration, empowering developers to create powerful applications while remaining free from the distractions of managing the underlying infrastructure. As a result, teams can achieve higher productivity and innovation in their data processing initiatives.

What is Akka?

Akka is an enterprise runtime and agentic AI platform built for organizations that need complex systems to stay reliable in production. The platform is based on years of production use across high-scale domains such as payments, banking, streaming, real-time analytics, long-running workflows, digital twins, edge relays, and distributed device coordination. Akka’s core runtime uses actor-based concurrency, clustering, in-memory state, sharding, event sourcing, durable execution, real-time streaming, backpressure, and active-active high availability. These capabilities support applications that need low-latency processing, resilient workflows, reliable message handling, replayable state, and recovery across node failures. Akka’s Agentic AI Platform applies the same reliability model to production AI systems, including agents, tools, orchestrations, integrations, memory, APIs, streaming, safeguards, evaluations, human approvals, and audit trails. Teams can use Akka Specify to turn functional requirements into versioned AI service specifications, while governance teams define risk controls, approval boundaries, evaluation matrices, and evidence requirements. Akka then generates, tests, runs, and certifies AI systems against both the development contract and the safeguard contract. Akka Verify helps validate what is actually running, prove conformance, and improve systems using production data. The platform is positioned as an alternative to stitching together separate frameworks, hyperscalers, memory tools, orchestration engines, guardrails, observability stacks, and governance products. Akka also emphasizes predictable annual pricing, cloud freedom, sovereign deployment options, 24/7 SRE support, active-active HA/DR, and enterprise-grade reliability commitments.

Media

Media

Integrations Supported

New Relic
CData Connect
DataBuck
Google Cloud Bigtable
Google Cloud Confidential VMs
Google Cloud Datastream
Google Cloud IoT Core
Google Cloud Knowledge Catalog
Google Cloud Managed Service for Apache Airflow
Google Cloud Platform
Google Cloud Profiler
Orchestra
Pantomath
Protegrity
Sedai
Telmai
Ternary

Integrations Supported

New Relic
AWS Marketplace
Dash
Sematext Cloud

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/dataflow

Company Facts

Organization Name

Akka

Date Founded

2011

Company Location

United States

Company Website

akka.io

Categories and Features

Data Engineering

Not specified

Data Pipeline

Not specified

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Categories and Features

Agentic AI

Not specified

Digital Twin

Not specified

Popular Alternatives

Apache Beam Reviews & Ratings

Apache Beam

Apache Software Foundation

Popular Alternatives