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DBMS > BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. JaguarDB

System Properties Comparison BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. JaguarDB

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonJaguarDB  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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Performant, highly scalable DBMS for AI and IoT applications
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
Wide column store
Relational DBMSKey-value store
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Websitebigobject.iowww.esgyn.cncloud.google.com/­bigtablecloud.google.com/­spannerwww.jaguardb.com
Technical documentationdocs.bigobject.iocloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docswww.jaguardb.com/­support.html
DeveloperBigObject, Inc.EsgynGoogleGoogleDataJaguar, Inc.
Initial release20152015201520172015
Current release3.3 July 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialcommercialOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++ infothe server part. Clients available in other languages
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedhostedLinux
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nonononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infoQuery statements complying to ANSI 2011A subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
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)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresLuaJava Stored Proceduresnonono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingSharding
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 zonesMulti-source replication with 3 replicas for regional instances.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes infousing Google Cloud Dataflowno
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 ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
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.yesnononono
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)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accounts

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More resources
BigObjectEsgynDBGoogle Cloud BigtableGoogle Cloud SpannerJaguarDB
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