Neo4j Keys

Link, Sebastian

doi:10.1007/978-3-030-62522-1_2

Cited by 9 publications

(7 citation statements)

References 18 publications

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“…An important popular class of object stores are graph databases, which also provide limited support for object integrity, in particular nodes. Similar to candidate keys, Neo4j keys require both existence and uniqueness for all properties of the key [32]. As a consequence, reasoning about these keys is not as intuitive as one may expect.…”

Section: Graph Modelsmentioning

confidence: 99%

“…A recent community effort has brought forward an expressive proposal for keys on property graphs, applicable to vertices, edges, and properties [2]. Around the same time, the concept of completeness-tailored uniqueness constraints was proposed for property graphs [42], following an earlier proposal of Neo4j keys in [32]. Noticeably, the keys of [32] and the mandatory PG-keys of [2] combine both existence and uniqueness constraints, while the uniqueness constraints of [42] and exclusive PG-keys of [2] separate them.…”

Section: Introductionmentioning

confidence: 99%

“…Around the same time, the concept of completeness-tailored uniqueness constraints was proposed for property graphs [42], following an earlier proposal of Neo4j keys in [32]. Noticeably, the keys of [32] and the mandatory PG-keys of [2] combine both existence and uniqueness constraints, while the uniqueness constraints of [42] and exclusive PG-keys of [2] separate them. The separation between existence and uniqueness constraints had already been made explicit in the context of SQL [46][47][48].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Uniqueness Constraints for Object Stores

Skavantzos

Leck

Zhao

et al. 2023

J. Data and Information Quality

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Object stores offer an increasingly popular choice for data management and analytics. As with every data model, managing the integrity of objects is fundamental for data quality but also important for the efficiency of update and query operations. In response to shortcomings of unique and existence constraints in object stores, we propose a new principled class of constraints that separates uniqueness from existence dimensions of data quality, and fully supports multiple labels and composite properties. We illustrate benefits of the constraints on real-world examples of property graphs where node integrity is enforced for better update and query performance. The benefits are quantified experimentally in terms of perfectly scaling the access to data through indices that result from the constraints. We establish axiomatic and algorithmic characterizations for the underlying implication problem. In addition, we fully characterize which non-redundant families of constraints attain maximum cardinality for any given finite sets of labels and properties. We exemplify further use cases of the constraints: elicitation of business rules, identification of data quality problems, and design for data quality. Finally, we propose extensions to managing the integrity of objects in object stores such as graph databases.

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Section: Graph Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Uniqueness Constraints for Object Stores

Skavantzos

Leck

Zhao

et al. 2023

J. Data and Information Quality

Self Cite

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show abstract

“…For the property graphs, a uniqueness constraint is a set of attributes whose values uniquely identify an entity in the collection. Neo4j keys [25] are based on uniqueness constraints and require the existence of such constraints for all vertices the graph. A new principled class of constraints called embedded uniqueness constraints have been proposed that separates uniqueness from existence dimensions and are used in the property graphs to uniquely identify entities [31].…”

Section: Related Workmentioning

confidence: 99%

Discovery of Keys for Graphs [Extended Version]

Alipourlangouri¹,

Chiang²

2022

Preprint

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Keys for graphs uses the topology and value constraints needed to uniquely identify entities in a graph database. They have been studied to support object identification, knowledge fusion, data deduplication, and social network reconciliation. In this paper, we present our algorithm to mine keys over graphs. Our algorithm discovers keys in a graph via frequent subgraph expansion. We present two properties that define a meaningful key, including minimality and support. Lastly, using real-world graphs, we experimentally verify the efficiency of our algorithm on real world graphs.

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“…A recent formalism [50] allows the definition of property-based key constraints solely on nodes and discusses its possible implementation on top of Neo4j using the Cypher language; that is, for a label and a set of properties, all the properties must exist in all the nodes with that label, and each combination of the values for these properties is unique for each node. It is also observed that such keys can be extended to nodes that carry multiple labels.…”

Section: Example 12 (Integrity In the Graphmentioning

confidence: 99%

PG-Keys: Keys for Property Graphs

Angles

Bonifati

Dumbrava

et al. 2021

Proceedings of the 2021 International Conference on Management of Data

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We report on a community effort between industry and academia to shape the future of property graph constraints. The standardization for a property graph query language is currently underway through the ISO Graph Query Language (GQL) project. Our position is that this project should pay close attention to schemas and constraints, and should focus next on key constraints.The main purposes of keys are enforcing data integrity and allowing the referencing and identifying of objects. Motivated by use cases from our industry partners, we argue that key constraints should be able to have different modes, which are combinations of basic restriction that require the key to be exclusive, mandatory, and singleton. Moreover, keys should be applicable to nodes, edges, and properties since these all can represent valid real-life entities. Our result is PG-Keys, a flexible and powerful framework for defining key constraints, which fulfills the above goals.PG-Keys is a design by the Linked Data Benchmark Council's Property Graph Schema Working Group, consisting of members from industry, academia, and ISO GQL standards group, intending to bring the best of all worlds to property graph practitioners. PG-Keys aims to guide the evolution of the standardization efforts towards making systems more useful, powerful, and expressive.

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Neo4j Keys

Cited by 9 publications

References 18 publications

Uniqueness Constraints for Object Stores

Uniqueness Constraints for Object Stores

Discovery of Keys for Graphs [Extended Version]

PG-Keys: Keys for Property Graphs

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