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DBMS > Badger vs. Databricks vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

System Properties Comparison Badger vs. Databricks vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.A fast-speed and highly-scalable Graph DBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelKey-value storeDocument store
Relational DBMS
Document storeGraph DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comfirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperDGraph LabsDatabricksGoogleBaiduCirconus LLC.
Initial release20172013201720182017
Current release0.9V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC and C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedhostedLinux
macOS
Unix
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes infotext, numeric, histograms
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.noyesnonono
Secondary indexesnoyesyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLnowith Databricks SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
Supported programming languagesGoPython
R
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Groovy
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes, in Lua
Triggersnoyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Users, roles and permissionsno
More information provided by the system vendor
BadgerDatabricksGoogle Cloud FirestoreHugeGraphIRONdb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
BadgerDatabricksGoogle Cloud FirestoreHugeGraphIRONdb
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