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DBMS > Databricks vs. Neo4j vs. Quasardb vs. Transwarp Hippo

System Properties Comparison Databricks vs. Neo4j vs. Quasardb vs. Transwarp Hippo

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNeo4j  Xexclude from comparisonQuasardb  Xexclude from comparisonTranswarp Hippo  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsDistributed, high-performance timeseries databaseCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelDocument store
Relational DBMS
Graph DBMSTime Series DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score0.05
Rank#386  Overall
#14  Vector DBMS
Websitewww.databricks.comneo4j.comquasar.aiwww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationdocs.databricks.comneo4j.com/­docsdoc.quasar.ai/­master
DeveloperDatabricksNeo4j, Inc.quasardb
Initial release2013200720092023
Current release5.20, May 20243.14.1, January 20241.0, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availablecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJava, ScalaC++C++
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
BSD
Linux
OS X
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free and schema-optionalschema-free
Typing infopredefined data types such as float or dateyesyes infointeger and binaryVector, Numeric and String
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnono
Secondary indexesyesyes infopluggable indexing subsystem, by default Apache Luceneyes infowith tagsno
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
HTTP APIRESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C++
Java
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoUser defined Procedures and Functionsnono
Triggersyes infovia event handlernono
Partitioning methods infoMethods for storing different data on different nodesyes using Neo4j FabricSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlySource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
User concepts infoAccess controlUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Cryptographically strong user authentication and audit trailRole based access control and fine grained access rights
More information provided by the system vendor
DatabricksNeo4jQuasardbTranswarp Hippo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Neo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
News

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8 June 2024

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4 June 2024

RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph
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This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more
1 June 2024

openCypher Will Pave the Road to GQL for Cypher Implementers
22 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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