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DBMS > BoltDB vs. IBM Db2 Event Store vs. Postgres-XL vs. Riak KV vs. Spark SQL

System Properties Comparison BoltDB vs. IBM Db2 Event Store vs. Postgres-XL vs. Riak KV vs. Spark SQL

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPostgres-XL  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn embedded key-value store for Go.Distributed Event Store optimized for Internet of Things use casesBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeEvent Store
Time Series DBMS
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­boltdb/­boltwww.ibm.com/­products/­db2-event-storewww.postgres-xl.orgspark.apache.org/­sql
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storewww.postgres-xl.org/­documentationwww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release201320172014 infosince 2012, originally named StormDB20092014
Current release2.010 R1, October 20183.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT Licensecommercial infofree developer edition availableOpen Source infoMozilla public licenseOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC and C++CErlangScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux infoLinux, macOS, Windows for the developer additionLinux
macOS
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesnoyes
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 infoXML type, but no XML query functionalitynono
Secondary indexesnonoyesrestrictedno
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimeyes infodistributed, parallel query executionnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesGoC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser defined functionsErlangno
Triggersnonoyesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneActive-active shard replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoMVCCnono
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes, using Riak Securityno

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More resources
BoltDBIBM Db2 Event StorePostgres-XLRiak KVSpark SQL
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