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DBMS > Databend vs. Drizzle vs. Google Cloud Bigtable vs. LeanXcale vs. Oracle Rdb

System Properties Comparison Databend vs. Drizzle vs. Google Cloud Bigtable vs. LeanXcale vs. Oracle Rdb

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLeanXcale  Xexclude from comparisonOracle Rdb  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.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityMySQL 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.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Key-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score1.14
Rank#178  Overall
#80  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­bigtablewww.leanxcale.comwww.oracle.com/­database/­technologies/­related/­rdb.html
Technical documentationdocs.databend.comcloud.google.com/­bigtable/­docswww.oracle.com/­database/­technologies/­related/­rdb-doc.html
DeveloperDatabend LabsDrizzle project, originally started by Brian AkerGoogleLeanXcaleOracle, originally developed by Digital Equipment Corporation (DEC)
Initial release20212008201520151984
Current release1.0.59, April 20237.2.4, September 20127.4.1.1, 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++
Server operating systemshosted
Linux
macOS
FreeBSD
Linux
OS X
hostedHP Open VMS
Data schemeyesyesschema-freeyesFlexible 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.nonono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsnoyes infothrough Apache Derbyyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
Java
Scala
Server-side scripts infoStored proceduresnonono
Triggersnono infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDAtomic single-row operationsACIDyes, on a single node
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.noyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DatabendDrizzleGoogle Cloud BigtableLeanXcaleOracle Rdb
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