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DBMS > Badger vs. Google Cloud Datastore vs. QuestDB vs. Sphinx vs. TempoIQ

System Properties Comparison Badger vs. Google Cloud Datastore vs. QuestDB vs. Sphinx vs. TempoIQ

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparisonTempoIQ infoformerly TempoDB  Xexclude from comparison
TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databasesScalable analytics DBMS for sensor data, provided as a service (SaaS)
Primary database modelKey-value storeDocument storeTime Series DBMSSearch engineTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#315  Overall
#46  Key-value stores
Score4.87
Rank#78  Overall
#12  Document stores
Score2.69
Rank#115  Overall
#8  Time Series DBMS
Score6.06
Rank#61  Overall
#6  Search engines
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastorequestdb.iosphinxsearch.comtempoiq.com (offline)
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsquestdb.io/­docssphinxsearch.com/­docs
DeveloperDGraph LabsGoogleQuestDB Technology IncSphinx Technologies Inc.TempoIQ
Initial release20172008201420012012
Current release3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava (Zero-GC), C++, RustC++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoschema-free via InfluxDB Line Protocolyesschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesnoyes
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.nononono
Secondary indexesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL with time-series extensionsSQL-like query language (SphinxQL)no
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocolHTTP API
Supported programming languagesGo.Net
Go
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#
Java
JavaScript infoNode.js
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Enginenonono
TriggersnoCallbacks using the Google Apps Enginenonoyes infoRealtime Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID for single-table writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 filesno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nosimple authentication-based access control
More information provided by the system vendor
BadgerGoogle Cloud DatastoreQuestDBSphinxTempoIQ infoformerly TempoDB
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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