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What is Google Cloud Bigtable?

Google Cloud Bigtable is a robust NoSQL data service that is fully managed and designed to scale efficiently, capable of managing extensive operational and analytical tasks. It offers impressive speed and performance, acting as a storage solution that can expand alongside your needs, accommodating data from a modest gigabyte to vast petabytes, all while maintaining low latency for applications as well as supporting high-throughput data analysis. You can effortlessly begin with a single cluster node and expand to hundreds of nodes to meet peak demand, and its replication features provide enhanced availability and workload isolation for applications that are live-serving. Additionally, this service is designed for ease of use, seamlessly integrating with major big data tools like Dataflow, Hadoop, and Dataproc, making it accessible for development teams who can quickly leverage its capabilities through support for the open-source HBase API standard. This combination of performance, scalability, and integration allows organizations to effectively manage their data across a range of applications.

What is DataOps DataFlow?

Apache Spark offers a comprehensive component-driven platform that streamlines the automation of Data Reconciliation testing for contemporary Data Lake and Cloud Data Migration initiatives. DataOps DataFlow serves as an innovative web-based tool designed to facilitate the automation of testing for ETL projects, Data Warehouses, and Data Migrations. You can utilize DataFlow to efficiently load data from diverse sources, perform comparisons, and transfer discrepancies either into S3 or a Database. This enables users to create and execute data flows with remarkable ease. It stands out as a premier testing solution specifically tailored for Big Data Testing. Moreover, DataOps DataFlow seamlessly integrates with a wide array of both traditional and cutting-edge data sources, encompassing RDBMS, NoSQL databases, as well as cloud-based and file-based systems, ensuring versatility in data handling.

Media

Media

Integrations Supported

Amazon Redshift
Auris
Azure Synapse Analytics
Datagaps DataOps Suite
Google Cloud Dataflow
Google Cloud IoT Core
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google VPC Service Controls
Hadoop
Heroic
InfluxDB
IntelliPay
JanusGraph
Peekdata
Privacera
Tableau
ThoughtSpot
TiMi
YepCode

Integrations Supported

Amazon Redshift
Auris
Azure Synapse Analytics
Datagaps DataOps Suite
Google Cloud Dataflow
Google Cloud IoT Core
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google VPC Service Controls
Hadoop
Heroic
InfluxDB
IntelliPay
JanusGraph
Peekdata
Privacera
Tableau
ThoughtSpot
TiMi
YepCode

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Contact us
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/bigtable

Company Facts

Organization Name

Datagaps

Date Founded

2010

Company Location

United States

Company Website

www.datagaps.com/dataops-dataflow/

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

NoSQL Database

Auto-sharding
Automatic Database Replication
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching
Multi-Model
Performance Management
Security Management

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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