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DBMS > Google Cloud Bigtable vs. HEAVY.AI vs. IBM Db2 warehouse vs. Lovefield vs. Splice Machine

System Properties Comparison Google Cloud Bigtable vs. HEAVY.AI vs. IBM Db2 warehouse vs. Lovefield vs. Splice Machine

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonLovefield  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareCloud-based data warehousing serviceEmbeddable relational database for web apps written in pure JavaScriptOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score2.30
Rank#127  Overall
#60  Relational DBMS
Score1.61
Rank#156  Overall
#71  Relational DBMS
Score0.35
Rank#286  Overall
#131  Relational DBMS
Score0.54
Rank#257  Overall
#118  Relational DBMS
Websitecloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
www.ibm.com/­products/­db2/­warehousegoogle.github.io/­lovefieldsplicemachine.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.heavy.aigithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsplicemachine.com/­how-it-works
DeveloperGoogleHEAVY.AI, Inc.IBMGoogleSplice Machine
Initial release20152016201420142014
Current release5.10, January 20222.1.12, February 20173.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAJavaScriptJava
Server operating systemshostedLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.nonono infoImport/export of XML data possibleno
Secondary indexesnonoyesyesyes
SQL infoSupport of SQLnoyesyesSQL-like query language infovia JavaScript builder patternyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
.NET Client API
JDBC
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoPL/SQL, SQL PLnoyes infoJava
TriggersnonoyesUsing read-only observersyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infousing MemoryDByes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM Db2 warehouse infoformerly named IBM dashDBLovefieldSplice Machine
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