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DBMS > Apache Impala vs. Datomic vs. Faircom DB vs. GeoSpock

System Properties Comparison Apache Impala vs. Datomic vs. Faircom DB vs. GeoSpock

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoSpock  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Spatial and temporal data processing engine for extreme data scale
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Websiteimpala.apache.orgwww.datomic.comwww.faircom.com/­products/­faircom-dbgeospock.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectFairCom CorporationGeoSpock
Initial release201320121979
Current release4.1.0, June 20221.0.6735, June 2023V12, November 20202.0, September 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureANSI C, C++Java, Javascript
Server operating systemsLinuxAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hosted
Data schemeyesyesschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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 indexesyesyesyestemporal, categorical
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes, ANSI SQL with proprietary extensionsANSI SQL for query only (using Presto)
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyes info.Net, JavaScript, C/C++no
TriggersnoBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDtunable from ACID to Eventually Consistentno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Yes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users can be defined per table

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More resources
Apache ImpalaDatomicFaircom DB infoformerly c-treeACEGeoSpock
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