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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  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.Operational and transactional Enterprise NoSQL database
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
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
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Websiteimpala.apache.orgcloud.google.com/­bigtablewww.progress.com/­marklogic
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docswww.progress.com/­marklogic/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerGoogleMarkLogic Corp.
Initial release2013200820152001
Current release4.1.0, June 20227.2.4, September 201211.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeyesyesschema-freeschema-free infoSchema can be enforced
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.nonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsnoyes infoSQL92
APIs and other access methodsJDBC
ODBC
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes infovia XQuery or JavaScript
Triggersnono infohooks for callbacks inside the server can be used.noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
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 zonesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transaction
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, with Range Indexes
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)Role-based access control at the document and subdocument levels

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More resources
Apache ImpalaDrizzleGoogle Cloud BigtableMarkLogic
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