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DBMS > Bangdb vs. Dolt vs. Hazelcast vs. Postgres-XL

System Properties Comparison Bangdb vs. Dolt vs. Hazelcast vs. Postgres-XL

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDolt  Xexclude from comparisonHazelcast  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphA MySQL compatible DBMS with Git-like versioning of data and schemaA widely adopted in-memory data gridBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSDocument storeDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitebangdb.comgithub.com/­dolthub/­dolt
www.dolthub.com
hazelcast.comwww.postgres-xl.org
Technical documentationdocs.bangdb.comdocs.dolthub.comhazelcast.org/­imdg/­docswww.postgres-xl.org/­documentation
DeveloperSachin Sinha, BangDBDoltHub IncHazelcast
Initial release2012201820082014 infosince 2012, originally named StormDB
Current releaseBangDB 2.0, October 20215.3.6, November 202310 R1, October 2018
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++GoJavaC
Server operating systemsLinuxLinux
macOS
Windows
All OS with a Java VMLinux
macOS
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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.nonoyes infothe object must implement a serialization strategyyes infoXML type, but no XML query functionality
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes
SQL infoSupport of SQLSQL like support with command line toolyesSQL-like query languageyes infodistributed, parallel query execution
APIs and other access methodsProprietary protocol
RESTful HTTP API
CLI Client
HTTP REST
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Java
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyes infocurrently in alpha releaseyes infoEvent Listeners, Executor Servicesuser defined functions
Triggersyes, Notifications (with Streaming only)yesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmnoneShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.yes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modeyesno
User concepts infoAccess controlyes (enterprise version only)Only one user is configurable, and must be specified in the config file at startupRole-based access controlfine grained access rights according to SQL-standard

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BangdbDoltHazelcastPostgres-XL
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