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DBMS > EsgynDB vs. Google Cloud Bigtable vs. KeyDB vs. Teradata

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. KeyDB vs. Teradata

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKeyDB  Xexclude from comparisonTeradata  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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablegithub.com/­Snapchat/­KeyDB
keydb.dev
www.teradata.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.keydb.devdocs.teradata.com
DeveloperEsgynGoogleEQ Alpha Technology Ltd.Teradata
Initial release2015201520191984
Current releaseTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC++
Server operating systemsLinuxhostedLinuxhosted
Linux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
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.nononoyes
Secondary indexesyesnoyes infoby using the Redis Search moduleyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesnonoyes infoSQL 2016 + extensions
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocol infoRESP - REdis Serialization Protoco.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresJava Stored ProceduresnoLuayes infoUDFs, stored procedures, table functions in parallel
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoHashing
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 zonesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
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
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
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)simple password-based access control and ACLfine grained access rights according to SQL-standard

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More resources
EsgynDBGoogle Cloud BigtableKeyDBTeradata
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