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DBMS > EsgynDB vs. Google Cloud Bigtable vs. HarperDB vs. Infobright vs. Teradata Aster

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. HarperDB vs. Infobright vs. Teradata Aster

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonInfobright  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeRelational DBMSRelational DBMS
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
Score0.55
Rank#248  Overall
#38  Document stores
Score0.96
Rank#194  Overall
#91  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.harperdb.ioignitetech.com/­softwarelibrary/­infobrightdb
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docs
DeveloperEsgynGoogleHarperDBIgnite Technologies Inc.; formerly InfoBright Inc.Teradata
Initial release20152015201720052005
Current release3.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availablecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaNode.jsC
Server operating systemsLinuxhostedLinux
OS X
Linux
Windows
Linux
Data schemeyesschema-freedynamic schemayesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyesyes
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 infoin Aster File Store
Secondary indexesyesnoyesno infoKnowledge Grid Technology used insteadyes
SQL infoSupport of SQLyesnoSQL-like data manipulation statementsyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresJava Stored ProceduresnoCustom Functions infosince release 3.1noR packages
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusternoneSharding
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 infothe nodes on which a table resides can be definedSource-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonoyes infoSQL Map-Reduce Framework
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsAtomic execution of specific operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesno
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)Access rights for users and rolesfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesfine grained access rights according to SQL-standard

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More resources
EsgynDBGoogle Cloud BigtableHarperDBInfobrightTeradata Aster
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