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DBMS > Axibase vs. FatDB vs. Google Cloud Datastore vs. Hazelcast vs. IBM Db2 warehouse

System Properties Comparison Axibase vs. FatDB vs. Google Cloud Datastore vs. Hazelcast vs. IBM Db2 warehouse

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridCloud-based data warehousing service
Primary database modelTime Series DBMSDocument store
Key-value store
Document storeKey-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#292  Overall
#25  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financecloud.google.com/­datastorehazelcast.comwww.ibm.com/­products/­db2/­warehouse
Technical documentationcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docs
DeveloperAxibase CorporationFatCloudGoogleHazelcastIBM
Initial release20132012200820082014
Current release155855.3.6, November 2023
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#Java
Server operating systemsLinuxWindowshostedAll OS with a Java VMhosted
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesyes, details hereyesyes
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 strategyno infoImport/export of XML data possible
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServerSQL-like query language (GQL)SQL-like query languageyes
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
PHP
Python
R
Ruby
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresyesyes infovia applicationsusing Google App Engineyes infoEvent Listeners, Executor ServicesPL/SQL, SQL PL
Triggersyesyes infovia applicationsCallbacks using the Google Apps Engineyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication using Paxosyes infoReplicated Mapyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standard

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More resources
AxibaseFatDBGoogle Cloud DatastoreHazelcastIBM Db2 warehouse infoformerly named IBM dashDB
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