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DBMS > Badger vs. Google Cloud Datastore vs. Graph Engine vs. Kinetica vs. QuestDB

System Properties Comparison Badger vs. Google Cloud Datastore vs. Graph Engine vs. Kinetica vs. QuestDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonKinetica  Xexclude from comparisonQuestDB  Xexclude from comparison
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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully vectorized database across both GPUs and CPUsA high performance open source SQL database for time series data
Primary database modelKey-value storeDocument storeGraph DBMS
Key-value store
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastorewww.graphengine.iowww.kinetica.comquestdb.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docswww.graphengine.io/­docs/­manualdocs.kinetica.comquestdb.io/­docs
DeveloperDGraph LabsGoogleMicrosoftKineticaQuestDB Technology Inc
Initial release20172008201020122014
Current release7.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0
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 languageGo.NET and CC, C++Java (Zero-GC), C++, Rust
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hosted.NETLinuxLinux
macOS
Windows
Data schemeschema-freeschema-freeyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or datenoyes, details hereyesyesyes
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.nonononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like DML and DDL statementsSQL with time-series extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesGo.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
C++
Java
JavaScript (Node.js)
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnousing Google App Engineyesuser defined functionsno
TriggersnoCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoGPU vRAM or System RAMyes infothrough memory mapped files
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level
More information provided by the system vendor
BadgerGoogle Cloud DatastoreGraph Engine infoformer name: TrinityKineticaQuestDB
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
BadgerGoogle Cloud DatastoreGraph Engine infoformer name: TrinityKineticaQuestDB
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