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DBMS > Apache Impala vs. Graph Engine vs. Speedb vs. TimescaleDB

System Properties Comparison Apache Impala vs. Graph Engine vs. Speedb vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonSpeedb  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDBA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSGraph DBMS
Key-value store
Key-value storeTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score0.26
Rank#310  Overall
#45  Key-value stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteimpala.apache.orgwww.graphengine.iowww.speedb.iowww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.graphengine.io/­docs/­manualdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftSpeedbTimescale
Initial release2013201020202017
Current release4.1.0, June 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoApache Version 2.0; commercial license availableOpen 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++.NET and CC++C
Server operating systemsLinux.NETLinux
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnonumerics, 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.nononoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
F#
Visual Basic
C
C++
Go
Java
Perl
Python
Ruby
.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-reduceyesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaGraph Engine infoformer name: TrinitySpeedbTimescaleDB
Specific characteristicsSpeedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesSpeedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more
Licensing and pricing modelsOpen source - Speedb OSS is released under an Apache license and can be found on...
» more

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More resources
Apache ImpalaGraph Engine infoformer name: TrinitySpeedbTimescaleDB
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Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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Redis expands data management capabilities with Speedb acquisition – Blocks and Files
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TimescaleDB Is a Vector Database Now, Too
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Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

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
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provided by Google News



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