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DBMS > Apache Phoenix vs. GBase vs. Google Cloud Bigtable vs. GridGain vs. LeanXcale

System Properties Comparison Apache Phoenix vs. GBase vs. Google Cloud Bigtable vs. GridGain vs. LeanXcale

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonLeanXcale  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.GridGain is an in-memory computing platform, built on Apache IgniteA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Key-value store
Relational DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Websitephoenix.apache.orgwww.gbase.cncloud.google.com/­bigtablewww.gridgain.comwww.leanxcale.com
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.html
DeveloperApache Software FoundationGeneral Data Technology Co., Ltd.GoogleGridGain Systems, Inc.LeanXcale
Initial release20142004201520072015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019GBase 8a, GBase 8s, GBase 8cGridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, Java, PythonJava, C++, .Net
Server operating systemsLinux
Unix
Windows
LinuxhostedLinux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyesnoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesStandard with numerous extensionsnoANSI-99 for query and DML statements, subset of DDLyes infothrough Apache Derby
APIs and other access methodsJDBCADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
Java
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnoyes (compute grid and cache interceptors can be used instead)
Triggersnoyesnoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACIDACID
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.yesnoyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations

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More resources
Apache PhoenixGBaseGoogle Cloud BigtableGridGainLeanXcale
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