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DBMS > BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. TimescaleDB

System Properties Comparison BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. TimescaleDB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesEnterprise-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.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
Wide column store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#333  Overall
#146  Relational DBMS
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score5.33
Rank#72  Overall
#4  Time Series DBMS
Websitebigobject.iowww.esgyn.cncloud.google.com/­bigtablewww.timescale.com
Technical documentationdocs.bigobject.iocloud.google.com/­bigtable/­docsdocs.timescale.com
DeveloperBigObject, Inc.EsgynGoogleTimescale
Initial release2015201520152017
Current release2.13.0, November 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedLinux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresLuaJava Stored Proceduresnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesnonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
BigObjectEsgynDBGoogle Cloud BigtableTimescaleDB
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