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DBMS > Google BigQuery vs. Hypertable vs. Neo4j vs. RavenDB

System Properties Comparison Google BigQuery vs. Hypertable vs. Neo4j vs. RavenDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonHypertable  Xexclude from comparisonNeo4j  Xexclude from comparisonRavenDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionLarge scale data warehouse service with append-only tablesAn open source BigTable implementation based on distributed file systems such as HadoopScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSWide column storeGraph DBMSDocument store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitecloud.google.com/­bigqueryneo4j.comravendb.net
Technical documentationcloud.google.com/­bigquery/­docsneo4j.com/­docsravendb.net/­docs
DeveloperGoogleHypertable Inc.Neo4j, Inc.Hibernating Rhinos
Initial release2010200920072010
Current release0.9.8.11, March 20165.19, April 20245.4, July 2022
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoGPL version3, commercial licenses availableOpen Source infoAGPL version 3, commercial license available
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 languageC++Java, ScalaC#
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeschema-free and schema-optionalschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.no
Secondary indexesnorestricted infoonly exact value or prefix value scansyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLyesnonoSQL-like query language (RQL)
APIs and other access methodsRESTful HTTP/JSON APIC++ API
Thrift
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnoyes infoUser defined Procedures and Functionsyes
Triggersnonoyes infovia event handleryes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes using Neo4j FabricSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanoACIDACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)noUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Authorization levels configured per client per database
More information provided by the system vendor
Google BigQueryHypertableNeo4jRavenDB
Specific characteristicsNeo4j 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
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