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DBMS > Google Cloud Bigtable vs. Google Cloud Firestore vs. HugeGraph vs. Ignite vs. Tkrzw

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Firestore vs. HugeGraph vs. Ignite vs. Tkrzw

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.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 DBMSApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Wide column store
Document storeGraph DBMSKey-value store
Relational DBMS
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.85
Rank#51  Overall
#8  Document stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecloud.google.com/­bigtablefirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orgdbmx.net/­tkrzw
Technical documentationcloud.google.com/­bigtable/­docsfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docsapacheignite.readme.io/­docs
DeveloperGoogleGoogleBaiduApache Software FoundationMikio Hirabayashi
Initial release20152017201820152020
Current release0.9Apache Ignite 2.60.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Java, .NetC++
Server operating systemshostedhostedLinux
macOS
Unix
Linux
OS X
Solaris
Windows
Linux
macOS
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyesno
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.nononoyesno
Secondary indexesnoyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnononoANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Groovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes, with Cloud Functionsnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflowvia hugegraph-sparkyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsyesACIDACID
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.noyesyesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access 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 permissionsSecurity Hooks for custom implementationsno

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More resources
Google Cloud BigtableGoogle Cloud FirestoreHugeGraphIgniteTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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