Apache Avro
Apache Avro is a data serialization system. (by apache)
Apache Orc
Apache ORC - the smallest, fastest columnar storage for Hadoop workloads (by apache)
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Apache Avro | Apache Orc | |
---|---|---|
22 | 4 | |
2,764 | 654 | |
1.4% | 0.9% | |
9.7 | 9.4 | |
about 2 hours ago | about 18 hours ago | |
Java | Java | |
Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Apache Avro
Posts with mentions or reviews of Apache Avro.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-14.
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Open Table Formats Such as Apache Iceberg Are Inevitable for Analytical Data
Apache AVRO [1] is one but it has been largely replaced by Parquet [2] which is a hybrid row/columnar format
[1] https://avro.apache.org/
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Generating Avro Schemas from Go types
The most common format for describing schema in this scenario is Apache Avro.
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How do you update an existing avro schema using apache avro SchemaBuilder?
I am testing a new schema registry which loads and retrieves different kinds of avro schemas. In the process of testing, I need to create a bunch of different types of avro schemas. As it involves a lot of permutations, I decided to create the schema programmatically.I am using the apache avro SchemaBuilder to do so.
- The state of Apache Avro in Rust
- How people generate examples for multiple programming languages?
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gRPC on the client side
Other serialization alternatives have a schema validation option: e.g., Avro, Kryo and Protocol Buffers. Interestingly enough, gRPC uses Protobuf to offer RPC across distributed components:
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Understanding Azure Event Hubs Capture
Apache Avro is a data serialization system, for more information visit Apache Avro
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tl;dr of Data Contracts
Once things like JSON became more popular Apache Avro appeared. You can define Avro files which can then be generated into Python, Java C, Ruby, etc.. classes.
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In One Minute : Hadoop
Avro, a data serialization system based on JSON schemas.
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Events: Fat or Thin?
Supporting multiple versions of an event schema is a solved problem. Apache Avro with a published schema hash in a message header is one solution.
https://avro.apache.org/
Apache Orc
Posts with mentions or reviews of Apache Orc.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-01.
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Java Serialization with Protocol Buffers
The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto.
- Personal data of 120,000 Russian servicemen fighting in Ukraine made public
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AWS EMR Cost Optimization Guide
Data formatting is another place to make gains. When dealing with huge amounts of data, finding the data you need can take up a significant amount of your compute time. Apache Parquet and Apache ORC are columnar data formats optimized for analytics that pre-aggregate metadata about columns. If your EMR queries column intensive data like sum, max, or count, you can see significant speed improvements by reformatting data like CSVs into one of these columnar formats.
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Apache Hudi - The Streaming Data Lake Platform
The following stack captures layers of software components that make up Hudi, with each layer depending on and drawing strength from the layer below. Typically, data lake users write data out once using an open file format like Apache Parquet/ORC stored on top of extremely scalable cloud storage or distributed file systems. Hudi provides a self-managing data plane to ingest, transform and manage this data, in a way that unlocks incremental data processing on them.
What are some alternatives?
When comparing Apache Avro and Apache Orc you can also consider the following projects:
Protobuf - Protocol Buffers - Google's data interchange format
SBE - Simple Binary Encoding (SBE) - High Performance Message Codec
Apache Parquet - Apache Parquet
Apache Thrift - Apache Thrift
hudi - Upserts, Deletes And Incremental Processing on Big Data.
iceberg - Apache Iceberg
tape - A lightning fast, transactional, file-based FIFO for Android and Java.
gRPC - The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)
debezium - Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.