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

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

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonPlanetScale  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 PlatformCloud-based data warehousing serviceScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelTime Series DBMSDocument store
Key-value store
Document storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
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
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financecloud.google.com/­datastorewww.ibm.com/­products/­db2/­warehouseplanetscale.com
Technical documentationcloud.google.com/­datastore/­docsplanetscale.com/­docs
DeveloperAxibase CorporationFatCloudGoogleIBMPlanetScale
Initial release20132012200820142020
Current release15585
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#Go
Server operating systemsLinuxWindowshostedhostedDocker
Linux
macOS
Data schemeyesschema-freeschema-freeyesyes
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.nonono infoImport/export of XML data possible
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServerSQL-like query language (GQL)yesyes infowith proprietary extensions
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
.NET Client API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo
Java
PHP
Python
R
Ruby
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyes infovia applicationsusing Google App EnginePL/SQL, SQL PLyes infoproprietary syntax
Triggersyesyes infovia applicationsCallbacks using the Google Apps Engineyesyes
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 PaxosyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflownono
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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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)fine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
AxibaseFatDBGoogle Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDBPlanetScale
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