DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. DolphinDB vs. Google Cloud Bigtable vs. YDB

System Properties Comparison Apache Impala vs. DolphinDB vs. Google Cloud Bigtable vs. YDB

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 Bigtable  Xexclude from comparisonYDB  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSTime Series DBMSKey-value store
Wide column store
Document store
Relational DBMS
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
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websiteimpala.apache.orgwww.dolphindb.comcloud.google.com/­bigtablegithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationimpala.apache.org/­impala-docs.htmldocs.dolphindb.cn/­en/­help200/­index.htmlcloud.google.com/­bigtable/­docsydb.tech/­en/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDolphinDB, IncGoogleYandex
Initial release2013201820152019
Current release4.1.0, June 2022v2.00.4, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree community version availablecommercialOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
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
hostedLinux
Data schemeyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoSQL-like query language (YQL)
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
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesInternal replication in Colossus, and regional replication between two clusters in different zonesActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesAtomic single-row operationsACID
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 defined for Yandex Cloud users

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 BigtableYDB
Recent citations in the news

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

Personal Data Protection Service Initiates Probe into Yandex.Go App’s Data Processing
10 August 2023, Civil Georgia

Data leak from Russian delivery app shows dining habits of the secret police
3 April 2022, The Verge

Russian Court Sues Yandex CEO For LGBT Propaganda Case
3 January 2024, VOI.ID

Yandex code leak: Why hack of ‘Russian Google’s’ ranking factors has spooked the SEO industry
1 February 2023, The Indian Express

Russian secret police data leaked by food delivery app including where they live and what they eat...
4 April 2022, The US Sun

provided by Google News



Share this page

Featured Products

Milvus logo

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

Neo4j logo

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

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

Present your product here