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DBMS > Apache Impala vs. Drizzle vs. Google Cloud Bigtable vs. HyperSQL

System Properties Comparison Apache Impala vs. Drizzle vs. Google Cloud Bigtable vs. HyperSQL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  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 HadoopMySQL 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.Multithreaded, transactional RDBMS written in Java infoalso known as HSQLDB
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score3.23
Rank#93  Overall
#48  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablehsqldb.org
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docshsqldb.org/­web/­hsqlDocsFrame.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerGoogle
Initial release2013200820152001
Current release4.1.0, June 20227.2.4, September 20122.7.2, June 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercialOpen Source infobased on BSD license
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modes
Data schemeyesyesschema-freeyes
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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsnoyes
APIs and other access methodsJDBC
ODBC
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API infoJDBC via HTTP
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoJava, SQL
Triggersnono infohooks for callbacks inside the server can be used.noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic 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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache ImpalaDrizzleGoogle Cloud BigtableHyperSQL infoalso known as HSQLDB
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Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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28 November 2017, Datanami

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31 January 2022, InfoQ.com

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

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6 May 2015, VentureBeat

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24 October 2022, The Daily Swig

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14 November 2022, TheServerSide.com

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