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DBMS > Badger vs. EventStoreDB vs. ObjectBox vs. Solr vs. Teradata

System Properties Comparison Badger vs. EventStoreDB vs. ObjectBox vs. Solr vs. Teradata

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonEventStoreDB  Xexclude from comparisonObjectBox  Xexclude from comparisonSolr  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Industrial-strength, open-source database solution built from the ground up for event sourcing.Extremely fast embedded database for small devices, IoT and MobileA widely used distributed, scalable search engine based on Apache LuceneA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelKey-value storeEvent StoreObject oriented DBMSSearch engineRelational DBMS
Secondary database modelsTime Series DBMSSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score1.10
Rank#179  Overall
#1  Event Stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.eventstore.comobjectbox.iosolr.apache.orgwww.teradata.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdevelopers.eventstore.comdocs.objectbox.iosolr.apache.org/­resources.htmldocs.teradata.com
DeveloperDGraph LabsEvent Store LimitedObjectBox LimitedApache Software FoundationTeradata
Initial release20172012201720061984
Current release21.2, February 20219.6.0, April 2024Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2commercial
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 languageGoC and C++Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Windows
Android
iOS
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)hosted
Linux
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or datenoyesyes infosupports customizable data types and automatic typingyes
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.nonoyesyes
Secondary indexesnoyesyes infoAll search fields are automatically indexedyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoSolr Parallel SQL Interfaceyes infoSQL 2016 + extensions
APIs and other access methodsProprietary native APIJava API
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesGoC
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonoJava pluginsyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneonline/offline synchronization between client and serveryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnoyesyesfine grained access rights according to SQL-standard
More information provided by the system vendor
BadgerEventStoreDBObjectBoxSolrTeradata
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14 November 2023

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More resources
BadgerEventStoreDBObjectBoxSolrTeradata
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