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DBMS > Google Cloud Bigtable vs. HarperDB vs. IRONdb vs. SwayDB vs. WakandaDB

System Properties Comparison Google Cloud Bigtable vs. HarperDB vs. IRONdb vs. SwayDB vs. WakandaDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSwayDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelKey-value store
Wide column store
Document storeTime Series DBMSKey-value storeObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.60
Rank#244  Overall
#38  Document stores
Score0.04
Rank#387  Overall
#61  Key-value stores
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitecloud.google.com/­bigtablewww.harperdb.iowww.circonus.com/solutions/time-series-database/swaydb.simer.auwakanda.github.io
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docsdocs.circonus.com/irondb/category/getting-startedwakanda.github.io/­doc
DeveloperGoogleHarperDBCirconus LLC.Simer PlahaWakanda SAS
Initial release20152017201720182012
Current release3.1, August 2021V0.10.20, January 20182.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialOpen Source infoGNU Affero GPL V3.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageNode.jsC and C++ScalaC++, JavaScript
Server operating systemshostedLinux
OS X
LinuxLinux
OS X
Windows
Data schemeschema-freedynamic schemaschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes infoJSON data typesyes infotext, numeric, histogramsnoyes
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 indexesnoyesnono
SQL infoSupport of SQLnoSQL-like data manipulation statementsSQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP APIRESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Kotlin
Scala
JavaScript
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1yes, in Luanoyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterAutomatic, metric affinity per nodenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsAtomic execution of specific operationsnoAtomic execution of operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesnonoyes

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More resources
Google Cloud BigtableHarperDBIRONdbSwayDBWakandaDB
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