A Survey of JSON-compatible Binary Serialization Specifications

Viotti, Juan Cruz; Kinderkhedia, Mital

doi:10.48550/arxiv.2201.02089

Cited by 5 publications

(33 citation statements)

References 73 publications

(149 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Given the JSON-compatible schema-less and schema-driven binary serialization specifications studied in [71], this benchmark aims to answer the following set of research questions:…”

Section: Space-efficiency Benchmark Studymentioning

confidence: 99%

“…The weight metrics for a JSON document are based on a common formula where C is the total number of data values in the JSON document and S is the total byte-size of the JSON document in minified form [71]:…”

Section: Content Typementioning

confidence: 99%

“…The selection of schema-driven and schema-less JSON-compatible binary serialization specifications is listed in Table 6 and Table 7. In comparison to our previous work [71], we use ASN-1Step 10.0.2 instead of 10.0.1, Microsoft Bond [43] 9.0.4 instead of 9.0.3, and Protocol Buffers [31] 3.15.3 instead of 3.13.0. None of these version upgrades involve changes to the encodings.…”

Section: Serialization Specificationsmentioning

confidence: 99%

“…Furthermore, we replaced the third-party BSON [42] Python implementation used in [71] with the Node.js official MongoDB implementation. We also replaced the Smile [55] Python implementation used in [71] with a Clojure implementation as we identified issues in the former implementation with respects to floating-point numbers. For example, encoding the floating-point number 282.55 results in 282.549988 when using pysmile v0.2.…”

Section: Serialization Specificationsmentioning

confidence: 99%

“…In [71], we discussed that schema-driven serialization specifications typically define custom schema languages that are not usable by any other schema-driven serialization specifications rather than relying on standardized schema languages such as JSON Schema [75]. The selection of schema-driven binary serialization specifications implement schema languages that are considered high-level as they abstractly describe data structures and depend on the serialization specification implementation to provide the corresponding encoding rules.…”

Section: Benchmarkmentioning

confidence: 99%

See 4 more Smart Citations

A Benchmark of JSON-compatible Binary Serialization Specifications

Viotti¹,

Kinderkhedia²

2022

Preprint

Self Cite

View full text Add to dashboard Cite

In this paper, we present a comprehensive benchmark of JSON-compatible binary serialization specifications using the SchemaStore open-source test suite collection of over 400 JSON documents matching their respective schemas and representative of their use across industries. We benchmark a set of schema-driven (ASN.1, Apache Avro, Microsoft Bond, Cap'n Proto, FlatBuffers, Protocol Buffers, and Apache Thrift) and schema-less (BSON, CBOR, FlexBuffers, MessagePack, Smile, and UBJSON) JSON-compatible binary serialization specifications. Existing literature on benchmarking JSON-compatible binary serialization specifications demonstrates extensive gaps when it comes to binary serialization specifications coverage, reproducibility and representativity, the role of data compression in binary serialization and the choice and use of obsolete versions of binary serialization specifications. We believe our work is the first of its kind to introduce a tiered taxonomy for JSON documents consisting of 36 categories classified as Tier 1, Tier 2 and Tier 3 as a common basis to class JSON documents based on their size, type of content, characteristics of their structure and redundancy criteria. We built and published a free-to-use online tool to automatically categorize JSON documents according to our taxonomy that generates related summary statistics. In the interest of fairness and transparency, we adhere to reproducible software development standards and publicly host the benchmark software and results on GitHub. Our findings provide a number of conclusions: sequential binary serialization specifications are typically more space-efficient than pointer-based binary serialization specifications independently of whether they are schema-less or schema-driven; in comparison to compressed JSON, both compressed and uncompressed schemaless binary serialization specifications result in negative median and average size reductions. Through our analysis, we find that both compressed and uncompressed schema-driven binary serialization specifications result in positive median and average reduction. Furthermore, compressed sequential schema-driven binary serialization specifications are strictly superior to compressed JSON in all the cases from the input data.

show abstract

“…Given the JSON-compatible schema-less and schema-driven binary serialization specifications studied in [71], this benchmark aims to answer the following set of research questions:…”

Section: Space-efficiency Benchmark Studymentioning

confidence: 99%

Section: Content Typementioning

confidence: 99%

Section: Serialization Specificationsmentioning

confidence: 99%

Section: Serialization Specificationsmentioning

confidence: 99%

Section: Benchmarkmentioning

confidence: 99%

See 3 more Smart Citations

A Benchmark of JSON-compatible Binary Serialization Specifications

Viotti¹,

Kinderkhedia²

2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

The Influence of the Nonfunctional Requirements on the Data Model

Kokrehel,

Bilicki

2024

Acta Cybern

View full text Add to dashboard Cite

During the design and development of real-world telemedicine applications, the data model evolves significantly along the datapath. The model itself, the storage technique, and the user interface are the most common contributors. This relates to non-functional requirements. The size and complexity of the domain model may also be significantly influenced by standards. This phenomenon is distinct from data model erosion, which occurs when the data model changes due to a software developer's fault and non-properly defined interfaces. This is occurring by design. We are unaware of any technique, including OMG's Unified Modeling Language (UML), that focuses on this aspect of complex systems: the change of the data model along the datapath. In this article, we investigate this phenomenon and, in addition to identifying the locations where this change may occur, we classify the modifications depending on the possible influence a specific model change may have on the system's overall properties. This paper presents a novel methodology for complex system datapath analysis and demonstrates its application to a selection of telemedicine-related applications. This technique illustrates the possible effect of non-functional requirements on the datapath and the potential consequences of these modifications.

show abstract

Lite2: A Schemaless Zero-Copy Serialization Format

Chen,

Guan,

Shuai

et al. 2024

Computers

View full text Add to dashboard Cite

In the field of data transmission and storage, serialization formats play a crucial role by converting complex data structures into a byte stream that can be easily stored, transmitted, and reconstructed. Despite the myriad available serialization formats, ranging from JSON to Protobuf, each has limitations, particularly in balancing schema flexibility, performance, and data copying overhead. This paper introduces Lite2, a novel data serialization format that addresses these challenges by combining schemaless flexibility with the efficiency of zero-copy operations for flat or key–value pair data types. Unlike traditional formats that often require a predefined schema and involve significant data copying during serialization and deserialization, Lite2 offers a dynamic schemaless approach that eliminates unnecessary data copying, optimizing system performance and efficiency. Built upon a contiguously stored B-tree structure, Lite2 enables efficient data lookup and modification without deserialization, thereby achieving zero-copy operations.

show abstract

A Survey of JSON-compatible Binary Serialization Specifications

Cited by 5 publications

References 73 publications

A Benchmark of JSON-compatible Binary Serialization Specifications

A Benchmark of JSON-compatible Binary Serialization Specifications

The Influence of the Nonfunctional Requirements on the Data Model

Lite2: A Schemaless Zero-Copy Serialization Format

Contact Info

Product

Resources

About