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

DBMS > Apache Impala vs. Brytlyt vs. Drizzle vs. Google Cloud Bigtable vs. Kinetica

System Properties Comparison Apache Impala vs. Brytlyt vs. Drizzle vs. Google Cloud Bigtable vs. Kinetica

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteimpala.apache.orgbrytlyt.iocloud.google.com/­bigtablewww.kinetica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.brytlyt.iocloud.google.com/­bigtable/­docsdocs.kinetica.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytDrizzle project, originally started by Brian AkerGoogleKinetica
Initial release20132016200820152012
Current release4.1.0, June 20225.0, August 20237.2.4, September 20127.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++ and CUDAC++C, C++
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
OS X
hostedLinux
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infowith proprietary extensionsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnonouser defined functions
Triggersnoyesno infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyesno
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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-row operationsno
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.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level

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 ImpalaBrytlytDrizzleGoogle Cloud BigtableKinetica
DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

London data analytics startup Brytlyt raises €4.43M from Amsterdam-based Finch Capital, others
22 December 2021, Silicon Canals

Brytlyt becomes NVIDIA Inception Premier Partner
31 January 2023, PR Newswire

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

Brytlyt raises £3.8m for '1000x faster analytics'
22 December 2021, BusinessCloud

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 introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica Delivers Real-Time Vector Similarity Search
22 March 2024, Geospatial World

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

Milvus logo

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

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

Present your product here