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DBMS > EsgynDB vs. Google Cloud Bigtable vs. HarperDB vs. RDF4J

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. HarperDB vs. RDF4J

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.esgyn.cncloud.google.com/­bigtablewww.harperdb.iordf4j.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docsrdf4j.org/­documentation
DeveloperEsgynGoogleHarperDBSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2015201520172004
Current release3.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaNode.jsJava
Server operating systemsLinuxhostedLinux
OS X
Linux
OS X
Unix
Windows
Data schemeyesschema-freedynamic schemayes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyes
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoSQL-like data manipulation statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Java
PHP
Python
Server-side scripts infoStored proceduresJava Stored ProceduresnoCustom Functions infosince release 3.1yes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusternone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definednone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsAtomic execution of specific operationsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesno

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More resources
EsgynDBGoogle Cloud BigtableHarperDBRDF4J infoformerly known as Sesame
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