The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Great_expectations Alternatives
Similar projects and alternatives to great_expectations
-
-
Airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
airbyte
The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
-
superset
Apache Superset is a Data Visualization and Data Exploration Platform
-
dbt-core
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
-
dagster
An orchestration platform for the development, production, and observation of data assets.
-
grouparoo
Discontinued 🦘 The Grouparoo Monorepo - open source customer data sync framework
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
re_data
re_data - fix data issues before your users & CEO would discover them 😊
-
-
evidently
Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
-
-
BentoML
The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
-
jitsu
Jitsu is an open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days
-
-
castled
Discontinued Castled is an open source reverse ETL solution that helps you to periodically sync the data in your db/warehouse into sales, marketing, support or custom apps without any help from engineering teams
-
kedro-great
The easiest way to integrate Kedro and Great Expectations
-
-
deepchecks
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
-
soda-core
:zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
-
streamlit
Streamlit — A faster way to build and share data apps.
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better great_expectations alternative or higher similarity.
great_expectations reviews and mentions
Posts with mentions or reviews of great_expectations.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-24.
-
Data Quality at Scale with Great Expectations, Spark, and Airflow on EMR
Great Expectations (GE) is an open-source data validation tool that helps ensure data quality.
- Looking for Unit Testing framework in Database Migration Process
-
Soda Core (OSS) is now GA! So, why should you add checks to your data pipelines?
GE is arguably the most well known OSS alternative to Soda Core. The third option is deequ, originally developed and released in OSS by AWS. Our community has told us that Soda Core is different because it’s easy to get going and embed into data pipelines. And it also allows some of the check authoring work to be moved to other members of the data team. I'm sure there are also scenarios where Soda Core is not the best option. For example, when you only use Pandas dataframes or develop in Scala.
- Greatexpectations - Always know what to expect from your data.
- Greatexpectations – Always know what to expect from your data
-
Package for drift detection
great_expectations: https://github.com/great-expectations/great_expectations
-
[D] Do you use data engineering pipelines for real life projects?
For example I just found "Great Expectations" and "Kedro", "Flyte" and I was wondering at which point in time and project complexity should we choose one of these tools instead of the ancient cave man way?
-
Data pipeline suggestions
Testing: GreatExpectations
-
Where can I find free data engineering ( big data) projects online?
Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset
- [P] Deepchecks: an open-source tool for high standards validations for ML models and data.
-
A note from our sponsor - WorkOS
workos.com | 18 Apr 2024
Stats
Basic great_expectations repo stats
15
9,418
9.9
6 days ago
great-expectations/great_expectations is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of great_expectations is Python.
Popular Comparisons
- great_expectations VS evidently
- great_expectations VS kedro-great
- great_expectations VS deepchecks
- great_expectations VS re_data
- great_expectations VS streamlit
- great_expectations VS seldon-core
- great_expectations VS fastapi
- great_expectations VS metaflow
- great_expectations VS soda-core
- great_expectations VS feast
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com