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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Hive vs. HugeGraph

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Hive vs. HugeGraph

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionEnterprise-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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.data warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.hawkular.orghive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationcloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidecwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperEsgynGoogleCommunity supported by Red HatApache Software Foundation infoinitially developed by FacebookBaidu
Initial release20152015201420122018
Current release3.1.3, April 20220.9
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaJavaJava
Server operating systemsLinuxhostedLinux
OS X
Windows
All OS with a Java VMLinux
macOS
Unix
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nononono
Secondary indexesyesnonoyesyes infoalso supports composite index and range index
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTJDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C++
Java
PHP
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnonoyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobs
Triggersnonoyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on Cassandraselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyes infoquery execution via MapReducevia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnonoACID
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and rolesUsers, roles and permissions

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More resources
EsgynDBGoogle Cloud BigtableHawkular MetricsHiveHugeGraph
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