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DBMS > Databend vs. Google Cloud Spanner vs. Heroic vs. jBASE vs. TimesTen

System Properties Comparison Databend vs. Google Cloud Spanner vs. Heroic vs. jBASE vs. TimesTen

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHeroic  Xexclude from comparisonjBASE  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA robust multi-value DBMS comprising development tools and middlewareIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSTime Series DBMSMultivalue DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­spannergithub.com/­spotify/­heroicwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.databend.comcloud.google.com/­spanner/­docsspotify.github.io/­heroicdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.oracle.com/­database/­timesten-18.1
DeveloperDatabend LabsGoogleSpotifyRocket Software (formerly Zumasys)Oracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20212017201419911998
Current release1.0.59, April 20235.711 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJava
Server operating systemshosted
Linux
macOS
hostedAIX
Linux
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesoptionalyes
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.nononoyesno
Secondary indexesnoyesyes infovia Elasticsearchyes
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011noEmbedded SQL for jBASE in BASICyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Go
Java
JavaScript (Node.js)
Python
.Net
Basic
Jabbascript
Java
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnononoyesPL/SQL
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication with 3 replicas for regional instances.yesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoStrict serializable isolationnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelfine grained access rights according to SQL-standard

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More resources
DatabendGoogle Cloud SpannerHeroicjBASETimesTen
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