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DBMS > Brytlyt vs. Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. HarperDB

System Properties Comparison Brytlyt vs. Dgraph vs. EsgynDB vs. Google Cloud Datastore vs. HarperDB

Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.
Primary database modelRelational DBMSGraph DBMSRelational DBMSDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#292  Overall
#132  Relational DBMS
Score1.39
Rank#155  Overall
#15  Graph DBMS
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.55
Rank#243  Overall
#38  Document stores
Websitebrytlyt.iodgraph.iowww.esgyn.cncloud.google.com/­datastorewww.harperdb.io
Technical documentationdocs.brytlyt.iodgraph.io/­docscloud.google.com/­datastore/­docsdocs.harperdb.io/­docs
DeveloperBrytlytDgraph Labs, Inc.EsgynGoogleHarperDB
Initial release20162016201520082017
Current release5.0, August 20233.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAGoC++, JavaNode.js
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
LinuxhostedLinux
OS X
Data schemeyesschema-freeyesschema-freedynamic schema
Typing infopredefined data types such as float or dateyesyesyesyes, details hereyes infoJSON data types
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.yes infospecific XML-type available, but no XML query functionality.nononono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesnoyesSQL-like query language (GQL)SQL-like data manipulation statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoJava Stored Proceduresusing Google App EngineCustom Functions infosince release 3.1
TriggersyesnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSynchronous replication via RaftMulti-source replication between multi datacentersMulti-source replication using Paxosyes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesnoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, using LMDB
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-standardno infoPlanned for future releasesfine 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 roles

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More resources
BrytlytDgraphEsgynDBGoogle Cloud DatastoreHarperDB
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