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DBMS > Badger vs. Pinecone vs. QuestDB vs. Sphinx vs. Splice Machine

System Properties Comparison Badger vs. Pinecone vs. QuestDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonPinecone  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 managed, cloud-native vector databaseA 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 storeVector DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerwww.pinecone.ioquestdb.iosphinxsearch.comsplicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.pinecone.io/­docs/­overviewquestdb.io/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDGraph LabsPinecone Systems, IncQuestDB Technology IncSphinx Technologies Inc.Splice Machine
Initial release20172019201420012014
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-freeyes infoschema-free via InfluxDB Line Protocolyesyes
Typing infopredefined data types such as float or datenoString, Number, Booleanyesnoyes
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 indexesnonoyes 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 languagesGoPythonC 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 proceduresnononoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal 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 nodesnoneSource-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 Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID 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 controlnonoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BadgerPineconeQuestDBSphinxSplice Machine
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
BadgerPineconeQuestDBSphinxSplice Machine
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