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DBMS > Badger vs. Microsoft Azure Table Storage vs. QuestDB vs. Sphinx vs. Splice Machine

System Properties Comparison Badger vs. Microsoft Azure Table Storage vs. QuestDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A Wide Column Store for rapid development using massive semi-structured datasetsA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeWide column storeTime Series DBMSSearch engineRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#328  Overall
#48  Key-value stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Score2.81
Rank#98  Overall
#7  Time Series DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerazure.microsoft.com/­en-us/­services/­storage/­tablesquestdb.iosphinxsearch.comsplicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerquestdb.io/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDGraph LabsMicrosoftQuestDB Technology IncSphinx Technologies Inc.Splice Machine
Initial release20172012201420012014
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava (Zero-GC), C++, RustC++Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoschema-free via InfluxDB Line Protocolyesyes
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.nonono
Secondary indexesnononoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL with time-series extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonononoyes infoJava
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with eventual consistencynoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID for single-table writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infothrough memory mapped filesyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BadgerMicrosoft Azure Table StorageQuestDBSphinxSplice Machine
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