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DBMS > EsgynDB vs. Google Cloud Bigtable vs. GridGain vs. Hazelcast

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. GridGain vs. Hazelcast

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonHazelcast  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.GridGain is an in-memory computing platform, built on Apache IgniteA widely adopted in-memory data grid
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value store
Relational DBMS
Key-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Websitewww.esgyn.cncloud.google.com/­bigtablewww.gridgain.comhazelcast.com
Technical documentationcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmlhazelcast.org/­imdg/­docs
DeveloperEsgynGoogleGridGain Systems, Inc.Hazelcast
Initial release2015201520072008
Current releaseGridGain 8.5.15.3.6, November 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava, C++, .NetJava
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
All OS with a Java VM
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyesyes infothe object must implement a serialization strategy
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoANSI-99 for query and DML statements, subset of DDLSQL-like query language
APIs and other access methodsADO.NET
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
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes (compute grid and cache interceptors can be used instead)yes infoEvent Listeners, Executor Services
Triggersnonoyes (cache interceptors and events)yes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
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 zonesyes (replicated cache)yes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
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)Security Hooks for custom implementationsRole-based access control

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More resources
EsgynDBGoogle Cloud BigtableGridGainHazelcast
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