LabVIEW alternatives for data acquisition

LabVIEW has long been the default way to program NI data acquisition hardware. NI currently sells LabVIEW Base, Full and Professional, plus the LabVIEW+ Suite bundle, as annual subscriptions or perpetual licenses with no feature difference between the two terms. LabVIEW Community Edition is free, but NI restricts it to personal, non-commercial, non-industrial use, and it cannot be used for teaching or research at a degree-granting institution.

A LabVIEW seat for every engineer who needs to take a measurement adds up. VIs are binary files, so they are hard to diff and review in the same tools as the rest of a team’s code. And much DAQ work is configuring channels, watching them and logging them, which doesn’t need a programming environment.

Configuration-based loggers

NI FlexLogger

FlexLogger is NI’s logger for people who want to record channels without programming. It detects NI-DAQmx hardware, lets you configure channels from menus, builds screens from prebuilt charts and indicators, and logs to CSV or TDMS. According to NI, FlexLogger Lite is free with no time limit and included with NI DAQ hardware. FlexLogger Professional, sold as a subscription or perpetual license, adds math and analysis channels, event triggers that control logging and outputs, an operator mode that locks the interface, and plug-ins written in LabVIEW or Python. Plug-ins are also how FlexLogger reaches anything outside NI-DAQmx. It is Windows software, and the 2023 readmes had already dropped 32-bit Windows and everything older than Windows 10.

If your hardware is cDAQ or PXI and your tests are mostly sensor logging, start here before writing any LabVIEW.

DewesoftX

Dewesoft’s software comes with its hardware: DewesoftX Professional is included free with Dewesoft DAQ systems, with the license stored on the device, and analysis mode for reviewing recorded files needs no license at all. Beyond its own instruments, DewesoftX reads Vector CAN interfaces, OxTS and GeneSys GPS/IMU units, FLIR and GigE cameras, OPC UA, Siemens S7 and Modbus TCP. It exports to more than 25 formats, including Excel, MATLAB, CSV, ASAM MDF, UNV and WAV. Dewesoft lists Windows 7, 10 and 11 as supported. It makes the most sense when you are buying Dewesoft hardware anyway.

DASYLab

DASYLab, sold by MCC and Digilent, wires measurement modules together on a worksheet: inputs, filters, FFTs, control logic, displays and file writers. Its data sheet lists drivers for more than 20 vendors including MCC, Data Translation and NI-DAQmx, plus Modbus, OPC, MQTT and GPIB, and it saves ASCII, TDM/TDMS or its own binary format. It runs on Windows. Pricing goes through distributors, and Farnell UK lists DASYLab Basic at £1,745 ex VAT at the time of writing. For live signal processing without text code, it is the closest thing to LabVIEW’s dataflow model on this list.

DAQFactory

AzeoTech’s DAQFactory leans toward HMI and process control: operator pages, a scripting language, alarms, and logging to ASCII, ODBC databases or binary files. It needs Windows 10 or later, and AzeoTech lists Lite at $299, Base at $599 and Pro at $1,199. LabJack documents it as a supported third-party application. AzeoTech’s own forum notes that its MCC and NI drivers are not kept current, so for NI hardware the other options here fit better.

Text languages: Python and MATLAB

Python with nidaqmx and vendor libraries

NI maintains nidaqmx, the official Python API for NI-DAQmx. It runs on Windows and on Linux distributions where NI-DAQmx is supported, needs the driver installed separately (python -m nidaqmx installdriver fetches it), and exposes the same tasks, channels, timing and triggering you would use from LabVIEW. It can also have the driver write TDMS directly while you read, which is how you keep high-rate logging off the Python side:

import nidaqmx
from nidaqmx.constants import AcquisitionType, LoggingMode, LoggingOperation

with nidaqmx.Task() as task:
    task.ai_channels.add_ai_voltage_chan("cDAQ1Mod1/ai0:3", min_val=-10, max_val=10)
    task.timing.cfg_samp_clk_timing(1000, sample_mode=AcquisitionType.CONTINUOUS)
    task.in_stream.configure_logging("run.tdms", LoggingMode.LOG_AND_READ,
                                     operation=LoggingOperation.CREATE_OR_REPLACE)
    task.start()
    for _ in range(60):  # about a minute at 1 kS/s
        block = task.read(number_of_samples_per_channel=1000)
        # block is a list per channel; check limits, update a plot, etc.

Other vendors publish their own bindings: labjack-ljm for LabJack T-series, uldaq and mcculw for MCC, the WaveForms SDK for Digilent’s Analog Discovery line, and PyVISA covers most SCPI instruments. With Python, the code is plain text in Git, test logic runs under pytest, and numpy, pandas and scipy analyze the data in the same process. You build the user interface, file handling and error recovery yourself. The Python data acquisition guide covers patterns that hold up on long runs.

MATLAB with Data Acquisition Toolbox

Data Acquisition Toolbox has support packages for NI-DAQmx devices, Measurement Computing hardware, Digilent Analog Discovery, the ADALM1000 and Windows sound cards. All of them are listed as Windows 64-bit only in R2026a. If your team already analyzes in MATLAB, acquiring there removes an export step, and the toolbox reads and writes TDMS too. Limits vary by vendor. The MCC package, for example, does not support counters, digital I/O or triggered acquisition.

Hardware test platforms: Synnax, Nominal and Sift

A newer group of companies builds software for organizations running many test stands, mostly in aerospace, defense and energy. They overlap with LabVIEW at the data and operations layer more than at the driver layer.

Synnax describes itself as one platform for real-time data acquisition, hardware control, visualization and analysis. It has drivers for NI, LabJack and Dewesoft hardware and for OPC UA, Modbus and EtherCAT, a domain-specific language called Arc for control sequences, and client libraries in Python, TypeScript and C++. The source is on GitHub under the Business Source License 1.1, its Console app runs on macOS and Windows, and the project is targeting a v1 release before the end of 2026.

Nominal sells a software suite to test and operate hardware: Nominal Core, a data platform for telemetry, video, logs and reports, and Nominal Connect, an edge application for Python-based test apps, hardware control and data capture that syncs when back online. It deploys in GovCloud, Azure Government, private cloud or on-premises, and its named customers include Anduril and Hermeus.

Sift is a telemetry platform that ingests, stores and analyzes hardware telemetry, with automated data review, anomaly detection and reporting. It targets aerospace, defense, energy, robotics and autonomous vehicles and offers cloud, on-premises, GovCloud and air-gapped deployments.

These platforms are built for programs with many stands, many engineers and traceability requirements, which is more infrastructure than a single bench with a few devices needs.

Where DAQAtlas fits

DAQAtlas, which is in development, sits between the configuration loggers and the platforms. It is a desktop app for macOS, Windows and Linux that records MCC, LabJack, Digilent and SCPI devices directly, and NI-DAQmx hardware through DAQAtlas Bridge, an agent on a Windows or Linux PC next to the NI hardware that streams it over the network. All devices record into one run with shared markers, and exports go to CSV, MATLAB, TDMS, Parquet or HDF5. It does not do real-time control, FPGA work or test sequencing, so it replaces LabVIEW only where LabVIEW was being used as a logger. Background on combining vendors is in running a mixed-vendor DAQ bench and synchronizing multiple DAQ devices. The beta list is open.

When LabVIEW is still the right tool

Deterministic control on CompactRIO or PXI uses the LabVIEW Real-Time and FPGA modules, and none of the tools above replace that. A lab with years of validated VIs, NI TestStand sequences that call them and engineers fluent in G gains little from a rewrite. Complex DAQmx timing, such as shared sample clocks across chassis, retriggerable acquisitions and hardware-timed single-point loops, is well documented in LabVIEW examples, though nidaqmx in Python calls the same driver. And if your organization already holds LabVIEW+ Suite seats, the marginal cost of one more LabVIEW logger is close to zero.

One middle path is to keep LabVIEW where it controls hardware and move the rest out of it, with FlexLogger or another logger for routine measurements, Python for automation and analysis, and TDMS or HDF5 files as the handoff. The file format guide compares how those formats move between tools.