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DBMS > Apache Impala vs. Axibase vs. FatDB vs. Google Cloud Datastore vs. Warp 10

System Properties Comparison Apache Impala vs. Axibase vs. FatDB vs. Google Cloud Datastore vs. Warp 10

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAxibase  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonWarp 10  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAnalytic DBMS for HadoopScalable 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 PlatformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSTime Series DBMSDocument store
Key-value store
Document storeTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score0.32
Rank#288  Overall
#25  Time Series DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.08
Rank#358  Overall
#35  Time Series DBMS
Websiteimpala.apache.orgaxibase.com/­docs/­atsd/­financecloud.google.com/­datastorewww.warp10.io
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAxibase CorporationFatCloudGoogleSenX
Initial release20132013201220082015
Current release4.1.0, June 202215585
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#Java
Server operating systemsLinuxLinuxWindowshostedLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infoshort, integer, long, float, double, decimal, stringyesyes, details hereyes
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.nononono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageno infoVia inetgration in SQL ServerSQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
JDBC
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
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
PHP
Python
R
Ruby
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes infovia applicationsusing Google App Engineyes infoWarpScript
Triggersnoyesyes infovia applicationsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationselectable replication factorMulti-source replication using Paxosselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual 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 infobased on HBase
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache ImpalaAxibaseFatDBGoogle Cloud DatastoreWarp 10
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