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DBMS > EsgynDB vs. etcd vs. Google Cloud Bigtable vs. HugeGraph vs. InterSystems Caché

System Properties Comparison EsgynDB vs. etcd vs. Google Cloud Bigtable vs. HugeGraph vs. InterSystems Caché

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA distributed reliable key-value storeGoogle'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 DBMSA multi-model DBMS and application server
Primary database modelRelational DBMSKey-value storeKey-value store
Wide column store
Graph DBMSKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score7.64
Rank#54  Overall
#5  Key-value stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score0.15
Rank#339  Overall
#33  Graph DBMS
Websitewww.esgyn.cnetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
www.intersystems.com/­products/­cache
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigtable/­docshugegraph.apache.org/­docsdocs.intersystems.com
DeveloperEsgynGoogleBaiduInterSystems
Initial release2015201520181997
Current release3.4, August 20190.92018.1.4, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0commercial
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 languageC++, JavaGoJava
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
hostedLinux
macOS
Unix
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesnonoyesyes
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.nonononoyes
Secondary indexesyesnonoyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesnononoyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
JSON over HTTP
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
C#
C++
Java
Server-side scripts infoStored proceduresJava Stored Proceduresnonoasynchronous Gremlin script jobsyes
Triggersnoyes, watching key changesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Internal replication in Colossus, and regional replication between two clusters in different zonesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic 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.nononoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsAccess rights for users, groups and roles

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More resources
EsgynDBetcdGoogle Cloud BigtableHugeGraphInterSystems Caché
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