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DBMS > Apache Impala vs. Badger vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

System Properties Comparison Apache Impala vs. Badger vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  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.
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.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 modelRelational DBMSKey-value storeDocument storeGraph DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score7.36
Rank#53  Overall
#9  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerfirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsGoogleBaiduCirconus LLC.
Initial release20132017201720182017
Current release4.1.0, June 20220.9V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJavaC and C++
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Unix
Linux
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes 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.nonononono
Secondary indexesyesnoyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLSQL-like DML and DDL statementsnononoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJDBC
ODBC
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCGoGo
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 proceduresyes infouser defined functions and integration of map-reducenoyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes, in Lua
Triggersnonoyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-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 methodsyes infoquery execution via MapReducenoUsing Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACIDno
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 controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess 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

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More resources
Apache ImpalaBadgerGoogle Cloud FirestoreHugeGraphIRONdb
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