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DBMS > Apache Phoenix vs. EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. WakandaDB

System Properties Comparison Apache Phoenix vs. EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. WakandaDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fast-speed and highly-scalable Graph DBMSWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Graph DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitephoenix.apache.orgwww.esgyn.cncloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
wakanda.github.io
Technical documentationphoenix.apache.orgcloud.google.com/­bigtable/­docshugegraph.apache.org/­docswakanda.github.io/­doc
DeveloperApache Software FoundationEsgynGoogleBaiduWakanda SAS
Initial release20142015201520182012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.92.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2.0Open Source infoAGPLv3, extended commercial license available
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 languageJavaC++, JavaJavaC++, JavaScript
Server operating systemsLinux
Unix
Windows
LinuxhostedLinux
macOS
Unix
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesyesyesnoyes infoalso supports composite index and range index
SQL infoSupport of SQLyesyesnonono
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
JavaScript
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresnoasynchronous Gremlin script jobsyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyesvia hugegraph-sparkno
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)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes infoedges in graph
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.yesnonoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsyes

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More resources
Apache PhoenixEsgynDBGoogle Cloud BigtableHugeGraphWakandaDB
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