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DBMS > Google Cloud Bigtable vs. H2 vs. Hazelcast vs. Splice Machine

System Properties Comparison Google Cloud Bigtable vs. H2 vs. Hazelcast vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonH2  Xexclude from comparisonHazelcast  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.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A widely adopted in-memory data gridOpen-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 DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecloud.google.com/­bigtablewww.h2database.comhazelcast.comsplicemachine.com
Technical documentationcloud.google.com/­bigtable/­docswww.h2database.com/­html/­main.htmlhazelcast.org/­imdg/­docssplicemachine.com/­how-it-works
DeveloperGoogleThomas MuellerHazelcastSplice Machine
Initial release2015200520082014
Current release2.2.220, July 20235.3.6, November 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoApache Version 2; commercial licenses availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemshostedAll OS with a Java VMAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyesSQL-like query languageyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Java.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Procedures and User-Defined Functionsyes infoEvent Listeners, Executor Servicesyes infoJava
Triggersnoyesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingShared 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 zonesWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes infoReplicated MapMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesYes, 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 Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)
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.noyesyesyes
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-standardRole-based access controlAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud BigtableH2HazelcastSplice Machine
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