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Database Entry

GrapheneDB


GrapheneDB is a cloud-based Database-as-a-Service provider for graph databases based on Neo4j. The cloud vendors it supports are Heroku and Amazon Web Services. It provides automatic and on-demand backups as well as 24/7 monitoring and help.[03][01]

Country of Origin
ES
Start Year
2012 [23]
Project Type
Commercial
Supported Languages
Java, PHP, Python, Ruby
Derived From
Neo4j
Inspired By
Neo4j
Compatible With
Neo4j
Operating System
Hosted

Database Entry

GrapheneDB


GrapheneDB is a cloud-based Database-as-a-Service provider for graph databases based on Neo4j. The cloud vendors it supports are Heroku and Amazon Web Services. It provides automatic and on-demand backups as well as 24/7 monitoring and help.[03][01]

History[04]


In 2012, the founder of GrapheneDB, Alberto Perdomo, wanted to use Neo4j for a project. The process of setting up and monitoring servers and finding a place to host it was challenging. Therefore, he decided to create GrapheneDB to make it easier for clients to focus on learning about Cypher and graph modeling in Neo4j as well as developing their applications.

Checkpoints[05][06]


GrapheneDB is a Database-as-a-Service provider that uses Neo4j. Neo4j uses non-block checkpoints, so it can be backed up as it serves user traffic. Neo4j can have daily or weekly full backups, which results in a database image on the disk. It also provides incremental backups that can be done hourly or daily. A combination of incremental and full backups allows for safety and efficiency. GrapheneDB also provides similar backups- daily, weekly, monthly, or on-demand backups. This also captures a current snapshot of the database for recovery (if needed) and doesn't require downtime.

Compression[07]


GrapheneDB uses "bit shaving" to compress the number of bits needed to store primitive types in arrays. This means that if an int array of size 4 has a a largest value of 4, it will only require 3 bits to write that 4. Therefore, each element in the array will be written in 3 bits to separate them from each other. The values are still "ints", but can be stored more efficiently. Similarly, if an int array contains -1, then that value will use the 32 bits required to write it, so each element in the array must also be written in 32 bits. It also has classes to limit the number of characters in each class. For example, the "Numerical, Date, and Hex" class have a 54 character count limit. This helps determine whether a string can be inlined or not, which allows for compression and less disk space required.

Concurrency Control[08]


Since GrapheneDB uses Neo4j as its graph database, it has the same concurrency control choices. Neo4j does deadlock detection and the transaction causing the deadlock is rolled back so the other transactions can continue. Neo4j allows the user to retry the transaction either by asking for the transaction to be attempted a certain number of times or through a retry loop.

Data Model[09][03][10]


Graphene is a Database-as-a-Service that uses Neo4j as the underlying graph database. Graph databases are good for data that are highly related to all the other data points as graph databases store data as nodes and the relationships between the nodes. Accessing nodes and getting relationships in a graph database is a constant time operation, which makes querying fast.

Foreign Keys[11]


In relational databases, a foreign key is a key that "joins" two tables in a JOIN. In graph databases, because relationships are just as important as the actual data, relationships and adjacent nodes are stored in the data itself, so foreign keys are not necessary in a graph database. The graphs uses the adjacent nodes and connections to access other data.

Indexes[12]


GrapheneDB uses B+ trees as its native index. The key size is limited, however, so if a transaction reaches the maximum key size, it will fail. A user can use Lucene as an index is the key size for the B+ index is limited. It can also support full text search by keeping all the data up to date automatically whenever new data or indexes are created.

Joins[13][14]


Neo4j uses HashJoin, with the build input being the left operator and the probe input being the right operator. The NodeHashJoin joins on the node ids whereas the ValueHashJoin joins on the data in two columns specified. Since GrapheneDB is a Database-as-a-Service that uses Neo4j, it has continued with this join choice as well.

Logging[15]


The Neo4j uses logical logging to recover the database after an unclean shutdown and for incremental backups. The recommended time to store logs is about 7 days.

Query Execution[16]


GrapheneDB uses Neo4j, which uses the tuple-at-a-time model as each operator in the tree takes in an input and first evaluates that. This output then goes into its parent operator as the input.

Query Interface[17][18]


Cypher is Neo4j's graph query language that lets user's store and get data from the graph database easily. GrapheneDB has also followed suit and uses Cypher. Cypher has similar functionalities as SQL since it was inspired by the SQL language. Cypher allows queries to be written efficiently as it can also select, insert, update, delete data without a description of how to do it.

Storage Architecture[19][20]


GrapheneDB stores its database on disk. It optimizes performance by storing information in a cache when possible.

Storage Model[21]


GrapheneDB uses Neo4j, which uses a custom storage model. Because Neo4j does not have a schema, each store file has the nodes, relationships, and key value properties. These are all stored at particular offsets in the files.

Stored Procedures[22]


A user can create a procedure using Cypher. The arguments when calling the function can either come from the query or from the associated parameter set.

Citations

23 sources
  1. GrapheneDB · The best way to run Neo4j graph databases in the Cloud. graphenedb.com
  2. https://www.graphenedb.com/docs graphenedb.com Dead — Check Archive
  3. What is a graph database - Getting Started neo4j.com
  4. Production-Grade Neo4j Hosting: Performance Ready neo4j.com
  5. https://docs.graphenedb.com/docs/backups graphenedb.com Dead — Check Archive
  6. https://d0.awsstatic.com/whitepapers/Database/neo4j-graph-databases-aws.pdf awsstatic.com Dead — Check Archive
  7. Performance - Operations Manual neo4j.com
  8. Transaction management - Java Reference neo4j.com
  9. GrapheneDB: Graph databases as-a-service | Product Hunt producthunt.com
  10. https://graphenedb.com/why-graphenedb.html graphenedb.com Dead — Check Archive
  11. Comparing relational to graph database - Getting Started neo4j.com
  12. Index configuration - Operations Manual neo4j.com
  13. Execution plans - Cypher Manual neo4j.com
  14. Operators - Cypher Manual neo4j.com
  15. Performance - Operations Manual neo4j.com
  16. Understanding query plans - Cypher Manual neo4j.com
  17. GrapheneDB Blog graphenedb.com
  18. Introduction - Cypher Manual neo4j.com
  19. https://docs.graphenedb.com/docs/plans-and-placements graphenedb.com Dead — Check Archive
  20. 9.5. Disks, RAM and other tips - Chapter 9. Performance neo4j.com
  21. Understanding Neo4j’s data on disk - Knowledge Base neo4j.com
  22. User-defined procedures - Java Reference neo4j.com
  23. https://www.crunchbase.com/organization/graphenedb#section-overview crunchbase.com
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