DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. DolphinDB vs. Google Cloud Datastore vs. Microsoft Azure Table Storage

System Properties Comparison Apache Impala vs. DolphinDB vs. Google Cloud Datastore vs. Microsoft Azure Table Storage

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDolphinDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSTime Series DBMSDocument storeWide column store
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteimpala.apache.orgwww.dolphindb.comcloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmldocs.dolphindb.cn/­en/­help200/­index.htmlcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDolphinDB, IncGoogleMicrosoft
Initial release2013201820082012
Current release4.1.0, June 2022v2.00.4, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community version availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemsLinuxLinux
Windows
hostedhosted
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, 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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesusing Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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 integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAdministrators, Users, GroupsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaDolphinDBGoogle Cloud DatastoreMicrosoft Azure Table Storage
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

Best cloud storage of 2024
4 June 2024, TechRadar

Google Cloud Stops Exit Fees
12 January 2024, Spiceworks News and Insights

BigID Data Intelligence Platform Now Available on Google Cloud Marketplace
6 November 2023, PR Newswire

What is Google App Engine? | Definition from TechTarget
26 April 2024, TechTarget

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

provided by Google News

Working with Azure to Use and Manage Data Lakes
7 March 2024, Simplilearn

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to use Azure Table storage in .Net
14 January 2019, InfoWorld

Quick Guide to Azure Storage Pricing
16 May 2023, DevOps.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here