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DBMS > Google Cloud Bigtable vs. Ignite vs. IRONdb vs. Splice Machine

System Properties Comparison Google Cloud Bigtable vs. Ignite vs. IRONdb vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIgnite  Xexclude from comparisonIRONdb  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded 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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen-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
Key-value store
Relational DBMS
Time Series DBMSRelational 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
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecloud.google.com/­bigtableignite.apache.orgwww.circonus.com/solutions/time-series-database/splicemachine.com
Technical documentationcloud.google.com/­bigtable/­docsapacheignite.readme.io/­docsdocs.circonus.com/irondb/category/getting-startedsplicemachine.com/­how-it-works
DeveloperGoogleApache Software FoundationCirconus LLC.Splice Machine
Initial release2015201520172014
Current releaseApache Ignite 2.6V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen 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 languageC++, Java, .NetC and C++Java
Server operating systemshostedLinux
OS X
Solaris
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyes infotext, numeric, histogramsyes
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.noyesno
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like query language (Circonus Analytics Query Language: CAQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yes, in Luayes infoJava
Triggersnoyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeShared 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 zonesyes (replicated cache)configurable replication factor, datacenter awareMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)noYes, 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 per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, 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.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud BigtableIgniteIRONdbSplice Machine
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