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DBMS > EsgynDB vs. Google Cloud Bigtable vs. HarperDB vs. Postgres-XL vs. YDB

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. HarperDB vs. Postgres-XL vs. YDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonYDB  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.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeRelational DBMSDocument store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
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
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.harperdb.iowww.postgres-xl.orggithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docswww.postgres-xl.org/­documentationydb.tech/­en/­docs
DeveloperEsgynGoogleHarperDBYandex
Initial release2015201520172014 infosince 2012, originally named StormDB2019
Current release3.1, August 202110 R1, October 2018
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availableOpen Source infoMozilla public licenseOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaNode.jsC
Server operating systemsLinuxhostedLinux
OS X
Linux
macOS
Linux
Data schemeyesschema-freedynamic schemayesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyesyes
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.nononoyes infoXML type, but no XML query functionalityno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesnoSQL-like data manipulation statementsyes infodistributed, parallel query executionSQL-like query language (YQL)
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
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API (DynamoDB compatible)
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
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresJava Stored ProceduresnoCustom Functions infosince release 3.1user defined functionsno
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioningSharding
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 definedActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonono
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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsAtomic execution of specific operationsACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
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 rolesfine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
EsgynDBGoogle Cloud BigtableHarperDBPostgres-XLYDB
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