WeDataSphere
cube.js
| WeDataSphere | cube.js | |
|---|---|---|
| 7 | 90 | |
| 662 | 18,433 | |
| 0.3% | 0.8% | |
| 5.0 | 9.9 | |
| about 1 year ago | 4 days ago | |
| Rust | ||
| - | GNU General Public License v3.0 or later |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
WeDataSphere
cube.js
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10 of the Best Web Analytics Tools for React Websites
Cube is a headless business intelligence tool for building analytical web apps quickly and efficiently. Data modeling, access control, APIs, and caching are the four main features of Cube. It offers analytical API servers with query orchestration and multi-level caching capabilities.
- CubeJS – A Universal OSS Semantic Layer (Maturity?)
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Show HN: Trilogy – A Reusable, Composable SQL Experiment
Not a SQL replacement, but if you're looking for an open source semantic layer, Cube is the way to go [0]
0 - https://github.com/cube-js/cube
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Why you should keep an eye on Apache DataFusion and its community.
LanceDB, Cube.dev, InfluxData, Denormalized, and Greptime are building completely different products. What they have in common, though, is that their products are a database system at their core and they are also using DataFusion to build them.
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MQL – Client and Server to query your DB in natural language
I should have clarified. There's a large number of apps that are:
1. taking info strictly from SQL (e.g. information_schema, query history)
2. taking a user input / question
3. writing SQL to answer that question
An app like this is what I call "text-to-sql". Totally agree a better system would pull in additional documentation (which is what we're doing), but I'd no longer consider it "text-to-sql". In our case, we're not even directly writing SQL, but rather generating semantic layer queries (i.e. https://cube.dev/).
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Show HN: Spice.ai – materialize, accelerate, and query SQL data from any source
I'm not too familiar with https://cube.dev/ - but my initial impression is they are focused more on providing APIs backed by SQL. They have a SQL API that emulates the PostgreSQL wire protocol, whereas Spice implements Arrow and Flight SQL natively. Their pre-aggregations are a similar concept to Spice's data accelerators. It also looks like they have their own query language, whereas Spice is native SQL as well.
- Show HN: Delphi – Build customer-facing AI data apps (that work)
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Apache Superset
We use https://cube.dev/ as intermediate layer between data warehouse database and Superset (and other "terminal" apps for BI like report generators). You define your schema (metrics, dimensions, joins, calculated metrics etc) in cube and then access them by any tool that can connect to SQL db
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Need to reduce costs - which service to use?
also check out cube.dev. they can do the semantic layer and cache it so you are not hitting Snowflake all the time.
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Anyone with experience moving to Cube.dev + Metabase/Superset from Looker ?
We need metrics to live in source control with reviews. Metabase doesn't have a git integration for metrics, which is why we are convinced to use cube.dev as a semantic layer.
What are some alternatives?
hadoopcryptoledger - Hadoop Crypto Ledger - Analyzing CryptoLedgers, such as Bitcoin Blockchain, on Big Data platforms, such as Hadoop/Spark/Flink/Hive
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
risingwave - Stream processing and management platform.
Druid - Apache Druid: a high performance real-time analytics database.
linkis - Apache Linkis builds a computation middleware layer to facilitate connection, governance and orchestration between the upper applications and the underlying data engines.
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.