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DBMS > BoltDB vs. Fujitsu Enterprise Postgres vs. Hive vs. IRONdb vs. Kinetica

System Properties Comparison BoltDB vs. Fujitsu Enterprise Postgres vs. Hive vs. IRONdb vs. Kinetica

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn embedded key-value store for Go.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.data warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUs
Primary database modelKey-value storeRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitegithub.com/­boltdb/­boltwww.postgresql.fastware.comhive.apache.orgwww.circonus.com/solutions/time-series-database/www.kinetica.com
Technical documentationwww.postgresql.fastware.com/­product-manualscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-starteddocs.kinetica.com
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software Foundation infoinitially developed by FacebookCirconus LLC.Kinetica
Initial release2013201220172012
Current releaseFujitsu Enterprise Postgres 14, January 20223.1.3, April 2022V0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoCJavaC and C++C, C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Windows
All OS with a Java VMLinuxLinux
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes infotext, numeric, histogramsyes
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 indexesnoyesyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Thrift
HTTP APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesGo.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsyes infouser defined functions and integration of map-reduceyes, in Luauser defined functions
Triggersnoyesnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingAutomatic, metric affinity per nodeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationselectable replication factorconfigurable replication factor, datacenter awareSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and rolesnoAccess rights for users and roles on table level
More information provided by the system vendor
BoltDBFujitsu Enterprise PostgresHiveIRONdbKinetica
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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BoltDBFujitsu Enterprise PostgresHiveIRONdbKinetica
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