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DBMS > EventStoreDB vs. Google Cloud Bigtable vs. GridGain vs. Riak KV vs. Sadas Engine

System Properties Comparison EventStoreDB vs. Google Cloud Bigtable vs. GridGain vs. Riak KV vs. Sadas Engine

Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridGain  Xexclude from comparisonRiak KV  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.GridGain is an in-memory computing platform, built on Apache IgniteDistributed, fault tolerant key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelEvent StoreKey-value store
Wide column store
Key-value store
Relational DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.10
Rank#179  Overall
#1  Event Stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitewww.eventstore.comcloud.google.com/­bigtablewww.gridgain.comwww.sadasengine.com
Technical documentationdevelopers.eventstore.comcloud.google.com/­bigtable/­docswww.gridgain.com/­docs/­index.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperEvent Store LimitedGoogleGridGain Systems, Inc.OpenSource, formerly Basho TechnologiesSADAS s.r.l.
Initial release20122015200720092006
Current release21.2, February 2021GridGain 8.5.13.2.0, December 20228.0
License infoCommercial or Open SourceOpen SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editioncommercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetErlangC++
Server operating systemsLinux
Windows
hostedLinux
OS X
Solaris
Windows
Linux
OS X
AIX
Linux
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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.noyesnono
Secondary indexesnoyesrestrictedyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLnoyes
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 API
Native Erlang Interface
JDBC
ODBC
Proprietary protocol
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)Erlangno
Triggersnoyes (cache interceptors and events)yes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"horizontal 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)selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsyes, using Riak SecurityAccess rights for users, groups and roles according to SQL-standard

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More resources
EventStoreDBGoogle Cloud BigtableGridGainRiak KVSadas Engine
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