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DBMS > Drizzle vs. etcd vs. Google Cloud Bigtable vs. H2

System Properties Comparison Drizzle vs. etcd vs. Google Cloud Bigtable vs. H2

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonH2  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A distributed reliable key-value storeGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.
Primary database modelRelational DBMSKey-value storeKey-value store
Wide column store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score8.33
Rank#46  Overall
#30  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigtablewww.h2database.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigtable/­docswww.h2database.com/­html/­main.html
DeveloperDrizzle project, originally started by Brian AkerGoogleThomas Mueller
Initial release200820152005
Current release7.2.4, September 20123.4, August 20192.2.220, July 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2.0commercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)
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++GoJava
Server operating systemsFreeBSD
Linux
OS X
FreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VM
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyes
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 indexesyesnonoyes
SQL infoSupport of SQLyes infowith proprietary extensionsnonoyes
APIs and other access methodsJDBCgRPC
JSON over HTTP
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Server-side scripts infoStored proceduresnononoJava Stored Procedures and User-Defined Functions
Triggersno infohooks for callbacks inside the server can be used.yes, watching key changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Internal replication in Colossus, and regional replication between two clusters in different zonesWith clustering: 2 database servers on different computers operate on identical copies of a database
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
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 Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess 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
DrizzleetcdGoogle Cloud BigtableH2
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