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DBMS > Apache Impala vs. Google Cloud Datastore vs. Netezza vs. SAP Adaptive Server vs. STSdb

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. Netezza vs. SAP Adaptive Server vs. STSdb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSAP Adaptive Server infoformer name: Sybase ASE  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformData warehouse and analytics appliance part of IBM PureSystemsThe SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMSKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument storeSpatial DBMS infowith Boeing's Spatial Query Server
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score36.31
Rank#25  Overall
#17  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websiteimpala.apache.orgcloud.google.com/­datastorewww.ibm.com/­products/­netezzawww.sap.com/­products/­technology-platform/­sybase-ase.htmlgithub.com/­STSSoft/­STSdb4
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docshelp.sap.com/­docs/­SAP_ASE
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleIBMSAP, SybaseSTS Soft SC
Initial release20132008200019872011
Current release4.1.0, June 202216.04.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C#
Server operating systemsLinuxhostedLinux infoincluded in applianceAIX
HP-UX
Linux
Solaris
Unix
Windows
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes infoprimitive types and user defined types (classes)
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
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yesyesno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
OLE DB
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
C
C++
Cobol
Java
Java
Perl
PHP
Python
C#
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App EngineyesJava and Transact-SQLno
TriggersnoCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDno
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization conceptfine grained access rights according to SQL-standardno

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More resources
Apache ImpalaGoogle Cloud DatastoreNetezza infoAlso called PureData System for Analytics by IBMSAP Adaptive Server infoformer name: Sybase ASESTSdb
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