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DBMS > BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. JaguarDB vs. Splice Machine

System Properties Comparison BigObject vs. EsgynDB vs. Google Cloud Bigtable vs. JaguarDB vs. Splice Machine

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonJaguarDB  Xexclude from comparisonSplice Machine  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.Performant, highly scalable DBMS for AI and IoT applicationsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
Wide column store
Key-value store
Vector DBMS
Relational 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
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitebigobject.iowww.esgyn.cncloud.google.com/­bigtablewww.jaguardb.comsplicemachine.com
Technical documentationdocs.bigobject.iocloud.google.com/­bigtable/­docswww.jaguardb.com/­support.htmlsplicemachine.com/­how-it-works
DeveloperBigObject, Inc.EsgynGoogleDataJaguar, Inc.Splice Machine
Initial release20152015201520152014
Current release3.3 July 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercialcommercialOpen Source infoGPL V3.0Open Source infoAGPL 3.0, commercial license available
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++, JavaC++ infothe server part. Clients available in other languagesJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedLinuxLinux
OS X
Solaris
Windows
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.nononono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyes
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)
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuaJava Stored Proceduresnonoyes infoJava
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
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 replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes, multi-version concurrency control (MVCC)
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.yesnononoyes
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)rights management via user accountsAccess rights for users, groups and roles according to SQL-standard

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More resources
BigObjectEsgynDBGoogle Cloud BigtableJaguarDBSplice Machine
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