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DBMS > Apache Impala vs. JanusGraph vs. OrigoDB vs. TimescaleDB

System Properties Comparison Apache Impala vs. JanusGraph vs. OrigoDB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonOrigoDB  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017A fully ACID in-memory object graph databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSGraph DBMSDocument store
Object oriented DBMS
Time Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteimpala.apache.orgjanusgraph.orgorigodb.comwww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.janusgraph.orgorigodb.com/­docsdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaLinux Foundation; originally developed as Titan by AureliusRobert Friberg et alTimescale
Initial release201320172009 infounder the name LiveDB2017
Current release4.1.0, June 20220.6.3, February 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC#C
Server operating systemsLinuxLinux
OS X
Unix
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonono infocan be achieved using .NETyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
.NET Client API
HTTP API
LINQ
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
Python
.Net.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)horizontal partitioning infoclient side managed; servers are not synchronizedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsdepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUser authentification and security via Rexster Graph ServerRole based authorizationfine grained access rights according to SQL-standard

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More resources
Apache ImpalaJanusGraph infosuccessor of TitanOrigoDBTimescaleDB
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Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, azure.microsoft.com

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

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