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DBMS > Google Cloud Bigtable vs. HarperDB vs. Hypertable vs. Ignite

System Properties Comparison Google Cloud Bigtable vs. HarperDB vs. Hypertable vs. Ignite

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHypertable  Xexclude from comparisonIgnite  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.An open source BigTable implementation based on distributed file systems such as HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelKey-value store
Wide column store
Document storeWide column storeKey-value store
Relational DBMS
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
Score0.55
Rank#248  Overall
#38  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitecloud.google.com/­bigtablewww.harperdb.ioignite.apache.org
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docsapacheignite.readme.io/­docs
DeveloperGoogleHarperDBHypertable Inc.Apache Software Foundation
Initial release2015201720092015
Current release3.1, August 20210.9.8.11, March 2016Apache Ignite 2.6
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsC++C++, Java, .Net
Server operating systemshostedLinux
OS X
Linux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeschema-freedynamic schemaschema-freeyes
Typing infopredefined data types such as float or datenoyes infoJSON data typesnoyes
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
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnoSQL-like data manipulation statementsnoANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
C++ API
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1noyes (compute grid and cache interceptors can be used instead)
Triggersnononoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedselectable replication factor on file system levelyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesyes (compute grid and hadoop accelerator)
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 integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesnoSecurity Hooks for custom implementations

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More resources
Google Cloud BigtableHarperDBHypertableIgnite
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