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DBMS > Datomic vs. DuckDB vs. Ehcache vs. Google Cloud Bigtable

System Properties Comparison Datomic vs. DuckDB vs. Ehcache vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDuckDB  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAn embeddable, in-process, column-oriented SQL OLAP RDBMSA widely adopted Java cache with tiered storage optionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMSRelational DBMSKey-value storeKey-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Websitewww.datomic.comduckdb.orgwww.ehcache.orgcloud.google.com/­bigtable
Technical documentationdocs.datomic.comduckdb.org/­docswww.ehcache.org/­documentationcloud.google.com/­bigtable/­docs
DeveloperCognitectTerracotta Inc, owned by Software AGGoogle
Initial release2012201820092015
Current release1.0.7075, December 20231.0.0, June 20243.10.0, March 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoMIT LicenseOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++Java
Server operating systemsAll OS with a Java VMserver-lessAll OS with a Java VMhosted
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesnono
SQL infoSupport of SQLnoyesnono
APIs and other access methodsRESTful HTTP APIArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
JCachegRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesClojure
Java
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
JavaC#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonono
TriggersBy using transaction functionsnoyes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneSharding infoby using Terracotta ServerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneyes infoby using Terracotta ServerInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes infosupports JTA and can work as an XA resourceAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infousing a tiered cache-storage approachyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyesno
User concepts infoAccess controlnononoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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DatomicDuckDBEhcacheGoogle Cloud Bigtable
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