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DBMS > Badger vs. Hive vs. Newts vs. Splice Machine

System Properties Comparison Badger vs. Hive vs. Newts vs. Splice Machine

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonHive  Xexclude from comparisonNewts  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.data warehouse software for querying and managing large distributed datasets, built on HadoopTime Series DBMS based on CassandraOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerhive.apache.orgopennms.github.io/­newtssplicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercwiki.apache.org/­confluence/­display/­Hive/­Homegithub.com/­OpenNMS/­newts/­wikisplicemachine.com/­how-it-works
DeveloperDGraph LabsApache Software Foundation infoinitially developed by FacebookOpenNMS GroupSplice Machine
Initial release2017201220142014
Current release3.1.3, April 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaJavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
Thrift
HTTP REST
Java API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGoC++
Java
PHP
Python
JavaC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infobased on CassandraShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factorselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.nonoyes
User concepts infoAccess controlnoAccess rights for users, groups and rolesnoAccess rights for users, groups and roles according to SQL-standard

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BadgerHiveNewtsSplice Machine
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