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

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

Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolEnterprise-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 features
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Document storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
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
Websitedoris.apache.org
github.com/­apache/­doris
www.esgyn.cncloud.google.com/­bigtablewww.harperdb.iowww.postgres-xl.org
Technical documentationgithub.com/­apache/­doris/­wikicloud.google.com/­bigtable/­docsdocs.harperdb.io/­docswww.postgres-xl.org/­documentation
DeveloperApache Software Foundation, originally contributed from BaiduEsgynGoogleHarperDB
Initial release20172015201520172014 infosince 2012, originally named StormDB
Current release1.2.2, February 20233.1, August 202110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infofree community edition availableOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaNode.jsC
Server operating systemsLinuxLinuxhostedLinux
OS X
Linux
macOS
Data schemeyesyesschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesyesnoyes 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.nonononoyes infoXML type, but no XML query functionality
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesyesnoSQL-like data manipulation statementsyes infodistributed, parallel query execution
APIs and other access methodsJDBC
MySQL client
ADO.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
Supported programming languagesJavaAll 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
Server-side scripts infoStored proceduresuser defined functionsJava Stored ProceduresnoCustom Functions infosince release 3.1user defined functions
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-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 defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsAtomic execution of specific operationsACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine 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-standard

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More resources
Apache DorisEsgynDBGoogle Cloud BigtableHarperDBPostgres-XL
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