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features
design
support

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Description

Impler is an innovative open-source infrastructure for data importation, crafted to assist engineering teams in creating comprehensive data import solutions without the need to repeatedly start from scratch. It features an intuitive guided importer that leads users through seamless data upload processes, along with intelligent auto-mapping capabilities that match user file headers to designated columns, thereby minimizing the likelihood of errors. Additionally, it incorporates thorough validation checks to confirm that each cell conforms to established schemas and custom criteria. The platform includes validation hooks that empower developers to implement custom JavaScript for validating data against external databases, and it also boasts an Excel template generator that produces personalized templates tailored to specified columns. Furthermore, Impler facilitates the import of data accompanied by images, allowing users to seamlessly upload visual content alongside their data entries, while also providing an auto-import functionality that can automatically retrieve and import data on a pre-set schedule. This combination of features makes Impler a powerful tool for enhancing data import processes across various projects.

Description

Upsolver makes it easy to create a governed data lake, manage, integrate, and prepare streaming data for analysis. Only use auto-generated schema on-read SQL to create pipelines. A visual IDE that makes it easy to build pipelines. Add Upserts to data lake tables. Mix streaming and large-scale batch data. Automated schema evolution and reprocessing of previous state. Automated orchestration of pipelines (no Dags). Fully-managed execution at scale Strong consistency guarantee over object storage Nearly zero maintenance overhead for analytics-ready information. Integral hygiene for data lake tables, including columnar formats, partitioning and compaction, as well as vacuuming. Low cost, 100,000 events per second (billions every day) Continuous lock-free compaction to eliminate the "small file" problem. Parquet-based tables are ideal for quick queries.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS IoT SiteWise No 
Angular Yes 
Bubble Yes 
Eco No 
Google Sheets Yes 
HTML Yes 
Hive No 
JSON Yes 
JavaScript Yes 
Micromerce No 
Microsoft Excel Yes 
PuppyGraph No 
React Yes 
XML Yes 

Integrations

AWS IoT SiteWise Yes 
Angular No 
Bubble No 
Eco Yes 
Google Sheets No 
HTML No 
Hive Yes 
JSON No 
JavaScript No 
Micromerce Yes 
Microsoft Excel No 
PuppyGraph Yes 
React No 
XML No 

Pricing Details

$35 per month
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Impler

Founded

2023

Country

India

Website

impler.io

Vendor Details

Company Name

Upsolver

Founded

2014

Country

Israel

Website

www.upsolver.com

Product Features

Product Features

Big Data

Collaboration No 
Data Blends Yes 
Data Cleansing Yes 
Data Mining Yes 
Data Visualization No 
Data Warehousing No 
High Volume Processing Yes 
No-Code Sandbox Yes 
Predictive Analytics No 
Templates No 

Data Mining

Data Extraction No 
Data Visualization No 
Fraud Detection No 
Linked Data Management No 
Machine Learning No 
Predictive Modeling No 
Semantic Search No 
Statistical Analysis No 
Text Mining No 

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

Alternatives

Alternatives