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DBMS > Databend vs. Drizzle vs. Google Cloud Datastore vs. H2 vs. LevelDB

System Properties Comparison Databend vs. Drizzle vs. Google Cloud Datastore vs. H2 vs. LevelDB

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonH2  Xexclude from comparisonLevelDB  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score8.33
Rank#46  Overall
#30  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­datastorewww.h2database.comgithub.com/­google/­leveldb
Technical documentationdocs.databend.comcloud.google.com/­datastore/­docswww.h2database.com/­html/­main.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperDatabend LabsDrizzle project, originally started by Brian AkerGoogleThomas MuellerGoogle
Initial release20212008200820052011
Current release1.0.59, April 20237.2.4, September 20122.2.220, July 20231.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoBSD
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++JavaC++
Server operating systemshosted
Linux
macOS
FreeBSD
Linux
OS X
hostedAll OS with a Java VMIllumos
Linux
OS X
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereyesno
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.nononono
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like query language (GQL)yesno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresnonousing Google App EngineJava Stored Procedures and User-Defined Functionsno
Triggersnono infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication using PaxosWith clustering: 2 database servers on different computers operate on identical copies of a databasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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)fine grained access rights according to SQL-standardno

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More resources
DatabendDrizzleGoogle Cloud DatastoreH2LevelDB
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