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DBMS > Google Cloud Bigtable vs. Hawkular Metrics vs. Immudb vs. TypeDB

System Properties Comparison Google Cloud Bigtable vs. Hawkular Metrics vs. Immudb vs. TypeDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonImmudb  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.
Primary database modelKey-value store
Wide column store
Time Series DBMSKey-value storeGraph DBMS infoThe type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS infoThe data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS infoThe type-theoretic data model of TypeDB subsumes the relational database model.
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.24
Rank#295  Overall
#42  Key-value stores
Score0.65
Rank#230  Overall
#20  Graph DBMS
#9  Object oriented DBMS
#107  Relational DBMS
Websitecloud.google.com/­bigtablewww.hawkular.orggithub.com/­codenotary/­immudb
immudb.io
typedb.com
Technical documentationcloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.immudb.iotypedb.com/­docs
DeveloperGoogleCommunity supported by Red HatCodenotaryVaticle
Initial release2015201420202016
Current release1.2.3, April 20222.28.3, June 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava
Server operating systemshostedLinux
OS X
Windows
BSD
Linux
macOS
Solaris
Windows
z/OS
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyes
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 indexesnonoyesyes
SQL infoSupport of SQLnonoSQL-like syntaxno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTgRPC protocol
PostgreSQL wire protocol
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnononono
Triggersnoyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingno
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on CassandraSynchronous replication via raft
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACID
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Google Cloud BigtableHawkular MetricsImmudbTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Google Cloud BigtableHawkular MetricsImmudbTypeDB infoformerly named Grakn
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