Protobuf VS Boost.Serialization

Compare Protobuf vs Boost.Serialization and see what are their differences.

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Protobuf Boost.Serialization
177 -
64,574 118
0.8% 0.8%
10.0 6.7
4 days ago about 1 month ago
C++ C++
GNU General Public License v3.0 or later -
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.

Protobuf

Posts with mentions or reviews of Protobuf. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-05-28.

Boost.Serialization

Posts with mentions or reviews of Boost.Serialization. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Boost.Serialization yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing Protobuf and Boost.Serialization you can also consider the following projects:

FlatBuffers - FlatBuffers: Memory Efficient Serialization Library

cereal - A C++11 library for serialization

SBE - Simple Binary Encoding (SBE) - High Performance Message Codec

MessagePack - MessagePack implementation for C and C++ / msgpack.org[C/C++]

Magic Enum C++ - Static reflection for enums (to string, from string, iteration) for modern C++, work with any enum type without any macro or boilerplate code

Apache Parquet - Apache Parquet Java

Bond - Bond is a cross-platform framework for working with schematized data. It supports cross-language de/serialization and powerful generic mechanisms for efficiently manipulating data. Bond is broadly used at Microsoft in high scale services.

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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.
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