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DBMS > Apache Impala vs. Dolt vs. Google Cloud Datastore vs. SQream DB vs. ToroDB

System Properties Comparison Apache Impala vs. Dolt vs. Google Cloud Datastore vs. SQream DB vs. ToroDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDolt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSQream DB  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopA MySQL compatible DBMS with Git-like versioning of data and schemaAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platforma GPU-based, columnar RDBMS for big data analytics workloadsA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSDocument store
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.96
Rank#193  Overall
#90  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websiteimpala.apache.orggithub.com/­dolthub/­dolt
www.dolthub.com
cloud.google.com/­datastoresqream.comgithub.com/­torodb/­server
Technical documentationimpala.apache.org/­impala-docs.htmldocs.dolthub.comcloud.google.com/­datastore/­docsdocs.sqream.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDoltHub IncGoogleSQream Technologies8Kdata
Initial release20132018200820172016
Current release4.1.0, June 20222022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC++, CUDA, Haskell, Java, ScalaJava
Server operating systemsLinuxLinux
macOS
Windows
hostedLinuxAll OS with a Java 7 VM
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyes, ANSI Standard SQL Typesyes infostring, integer, double, boolean, date, object_id
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (GQL)yes
APIs and other access methodsJDBC
ODBC
CLI Client
HTTP REST
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.Net
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infocurrently in alpha releaseusing Google App Engineuser defined functions in Python
TriggersnoyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardinghorizontal and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Multi-source replication using PaxosnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowno
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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 KerberosOnly one user is configurable, and must be specified in the config file at startupAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
Apache ImpalaDoltGoogle Cloud DatastoreSQream DBToroDB
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