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DBMS > Apache Impala vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. Ingres

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. IBM Db2 Event Store vs. Ingres

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonIngres  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed Event Store optimized for Internet of Things use casesWell established RDBMS
Primary database modelRelational DBMSDocument storeEvent Store
Time Series DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Score3.63
Rank#79  Overall
#43  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­datastorewww.ibm.com/­products/­db2-event-storewww.actian.com/­databases/­ingres
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.actian.com/­ingres
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleIBMActian Corporation
Initial release2013200820171974 infooriginally developed at University Berkely in early 1970s
Current release4.1.0, June 20222.012.0, July 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree developer edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++C
Server operating systemsLinuxhostedLinux infoLinux, macOS, Windows for the developer additionAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, 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.nononono infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yes infothrough the embedded Spark runtimeyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineyesyes
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosActive-active shard replicationIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownono
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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes infoMVCC
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
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)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache ImpalaGoogle Cloud DatastoreIBM Db2 Event StoreIngres
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