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DBMS > Apache Impala vs. Google Cloud Bigtable vs. Google Cloud Firestore vs. Ignite vs. Tkrzw

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. Google Cloud Firestore vs. Ignite vs. Tkrzw

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonIgnite  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGoogle'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.Apache 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 modelRelational DBMSKey-value store
Wide column store
Document storeKey-value store
Relational DBMS
Key-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score7.85
Rank#51  Overall
#8  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteimpala.apache.orgcloud.google.com/­bigtablefirebase.google.com/­products/­firestoreignite.apache.orgdbmx.net/­tkrzw
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsfirebase.google.com/­docs/­firestoreapacheignite.readme.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleGoogleApache Software FoundationMikio Hirabayashi
Initial release20132015201720152020
Current release4.1.0, June 2022Apache Ignite 2.60.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, Java, .NetC++
Server operating systemsLinuxhostedhostedLinux
OS X
Solaris
Windows
Linux
macOS
Data schemeyesschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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 indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoANSI-99 for query and DML statements, subset of DDLno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, Firebase Rules & Cloud Functionsyes (compute grid and cache interceptors can be used instead)no
Triggersnonoyes, with Cloud Functionsyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesUsing Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsyesACID
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.nonoyesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess 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.Security Hooks for custom implementationsno

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More resources
Apache ImpalaGoogle Cloud BigtableGoogle Cloud FirestoreIgniteTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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