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DBMS > Apache Impala vs. QuestDB vs. Splice Machine vs. TerarkDB vs. TimesTen

System Properties Comparison Apache Impala vs. QuestDB vs. Splice Machine vs. TerarkDB vs. TimesTen

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonQuestDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTerarkDB  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA high performance open source SQL database for time series dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSTime Series DBMSRelational DBMSKey-value storeRelational 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
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteimpala.apache.orgquestdb.iosplicemachine.comgithub.com/­bytedance/­terarkdbwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationimpala.apache.org/­impala-docs.htmlquestdb.io/­docssplicemachine.com/­how-it-worksbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcdocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaQuestDB Technology IncSplice MachineByteDance, originally TerarkOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20132014201420161998
Current release4.1.0, June 20223.1, March 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial inforestricted open source version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustJavaC++
Server operating systemsLinuxLinux
macOS
Windows
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyes infoschema-free via InfluxDB Line Protocolyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesnoyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL with time-series extensionsyesnoyes
APIs and other access methodsJDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
Native Spark Datasource
ODBC
C++ API
Java API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesAll languages supporting JDBC/ODBCC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infoJavanoPL/SQL
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)Shared Nothhing Auto-Sharding, Columnar Partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication with eventual consistencyMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID for single-table writesACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped filesyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaQuestDBSplice MachineTerarkDBTimesTen
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache ImpalaQuestDBSplice MachineTerarkDBTimesTen
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